ESG Data & Reporting Manager

Role Purpose & Context

Role Summary

The ESG Data & Reporting Manager is responsible for building and running our entire ESG data collection, validation, and reporting function. You'll essentially be the chief architect and guardian of our sustainability numbers, making sure everything we publish is accurate, consistent, and auditable. You'll sit at the heart of our Sustainability_Corporate_Social team, translating complex regulatory requirements into practical data strategies and managing the team that makes it all happen. When this role is done well, our company's sustainability claims are seen as credible and trustworthy, protecting our reputation and attracting responsible investment. When it's not, we risk public embarrassment, regulatory fines, and a serious hit to our brand. The challenge is navigating ever-changing regulations and getting disparate data from across the business, often from people who don't report to you. The reward? Seeing your work directly influence investor confidence and genuinely help shape a more sustainable business.

Reporting Structure

• Reports to: Director of ESG & Sustainability
• Direct reports: Roughly 3-5 ESG Data Analysts/Specialists
• Matrix relationships: Head of ESG Data, Sustainability Data Lead, Manager, Corporate Responsibility Reporting, ESG Assurance Manager,

Key Stakeholders

Internal:

• Director of ESG & Sustainability
• Head of Investor Relations
• Finance Leadership (CFO, Financial Controller)
• IT & Data Governance Team
• Legal & Compliance
• Operations Directors (for facility data)
• HR Leadership (for DE&I data)

External:

• External Auditors (Big Four)
• ESG Rating Agencies (MSCI, Sustainalytics)
• Key Investors and Shareholders
• Regulators (e.g., FCA, EU Commission for CSRD)
• Sustainability Consultants

Organisational Impact

Scope: This role directly impacts our corporate reputation, investor relations, and regulatory compliance. You're building the data backbone that underpins all our sustainability claims, influencing everything from our share price to our ability to attract and retain talent. Getting this right means we can confidently tell our sustainability story; getting it wrong means we risk accusations of greenwashing and significant financial penalties.

Performance Metrics

Quantitative Metrics

1. Metric: ESG Data Audit Readiness Score
2. Desc: The percentage of our reported ESG data points that can be traced back to their original source with full documentation and sign-off, as assessed by internal or external pre-audit checks.
3. Target: >95% for all material disclosures
4. Freq: Quarterly (internal spot checks), Annually (pre-audit review)
5. Example: Before the annual audit, 98% of our Scope 1 & 2 emissions data points had clear data lineage, source documents, and internal approvals, leading to zero major findings from the external auditors.
6. Metric: ESG Rating Agency Score Improvement
7. Desc: Measurable improvement in our scores from key ESG rating agencies (e.g., MSCI, Sustainalytics) based on the quality and completeness of our data disclosures.
8. Target: Increase by 1-2 rating levels (e.g., MSCI 'A' to 'AA') within 24 months for 2 key agencies
9. Freq: Annually (post-rating publication)
10. Example: After implementing new data collection processes for human capital metrics, our Sustainalytics score for 'Social Capital' improved by 15 points, contributing to an overall upgrade from 'Medium Risk' to 'Low Risk'.
11. Metric: Reporting Cycle Time Reduction
12. Desc: The total elapsed time from the end of the reporting period to the final publication of our annual sustainability report, measured in working days.
13. Target: Reduce by 25% within 18 months (e.g., from 120 days to 90 days)
14. Freq: Annually (post-report publication)
15. Example: By automating several data aggregation steps and streamlining internal review cycles, we cut the report production time from 110 days to 85 days for the latest annual report.
16. Metric: Data Coverage & Granularity
17. Desc: The percentage of relevant operational sites, business units, and supply chain tiers for which we successfully collect primary ESG data, rather than relying on estimates.
18. Target: Increase primary data coverage by 15% across Scope 3 categories within 12 months
19. Freq: Bi-annually
20. Example: We increased primary data collection for our logistics emissions (Scope 3, Category 4) from 60% of transport providers to 75% by implementing a new data portal for suppliers.

Qualitative Metrics

1. Metric: Stakeholder Trust & Confidence
2. Desc: Our internal and external stakeholders (e.g., Investor Relations, auditors, board members) consistently express high confidence in the accuracy and reliability of our ESG data.
3. Evidence: You'll be proactively consulted on investor presentations and board reports that include ESG data. Auditors will complete their reviews with fewer queries and a smoother process. Internal teams will trust the data you provide without needing to double-check it themselves. You'll hear phrases like 'Ask [Your Name], they'll have the real numbers.'
4. Metric: Team Development & Empowerment
5. Desc: Your team feels supported, develops new skills, and takes increasing ownership of their respective data domains, contributing to a positive team culture.
6. Evidence: Team members will regularly ask for your guidance on complex data challenges, not just simple tasks. They'll proactively propose process improvements and take initiative on new projects. Retention rates for your direct reports will be strong, and they'll speak positively about their development opportunities. You'll see them mentoring junior colleagues effectively.
7. Metric: Strategic Data Integration
8. Desc: ESG data is effectively integrated into broader business decision-making processes and enterprise systems, moving beyond just reporting.
9. Evidence: ESG data points you oversee will be regularly referenced in strategic planning meetings, not just sustainability-specific ones. You'll be invited to discussions about new ERP module implementations to ensure ESG data capture. Finance will start asking for ESG data in their quarterly business reviews. You'll see evidence of ESG data influencing procurement decisions or product development.
10. Metric: Adaptability to Regulatory Change
11. Desc: The team demonstrates a proactive and organised approach to adapting our data collection and reporting processes to new or evolving ESG regulations (e.g., CSRD, SEC climate rules).
12. Evidence: When a new regulation drops, your team will have a clear plan for assessing its impact and adapting our systems, rather than reacting chaotically. You'll be able to articulate our readiness for upcoming regulatory changes to senior leadership. We won't be caught off guard by new disclosure requirements.

Primary Traits

• Trait: Meticulous Investigator
• Manifestation: You're the kind of person who can spot a single incorrect unit in a spreadsheet of thousands of entries. You won't just accept a number; you'll want to see the source document, understand the calculation, and check for any anomalies. When an auditor asks for the data lineage of a specific emissions figure from two years ago, you'll know exactly where to find the original utility bill and the calculation spreadsheet. Frankly, you enjoy the hunt for accuracy.
• Benefit: In ESG reporting, one tiny error can blow up into a massive reputational crisis or a failed audit. We're talking about figures that influence investor decisions worth millions, so the integrity of our data is paramount. Your meticulousness is our first and last line of defence against bad data and greenwashing accusations. You're not just checking boxes; you're safeguarding the company's credibility.
• Trait: Patient Persuader
• Manifestation: You'll spend a fair bit of time gently nudging colleagues in Operations, HR, or IT for data they might not prioritise. This means sending polite follow-ups, offering to help them extract the data, and patiently explaining *why* this information is crucial for the company, not just 'another ESG request.' You're good at building rapport, even with people who are constantly busy and under pressure.
• Benefit: The truth is, most of the data you need lives outside your direct team, and the people who hold it usually have other, more 'urgent' priorities. Your ability to build relationships, communicate the value of ESG data, and persistently (but politely) get what you need is absolutely critical. Without it, our data collection grinds to a halt, and we can't report anything meaningful.
• Trait: Healthy Skeptic
• Manifestation: When you see a sudden, dramatic improvement in a sustainability metric, your first thought isn't 'great job!' but 'what changed?'. You'll question if a perfect, round number is an estimate rather than a metered reading. You'll push back if someone tries to gloss over an inconsistency or wants to 'optimise' the data to look better. You're the one who asks the uncomfortable questions about data quality.
• Benefit: ESG data is notoriously messy, often based on estimates, and sometimes subject to internal pressure to look good. We need someone who can cut through the noise, challenge assumptions, and ensure that our reported numbers reflect reality, not just aspiration. Your skepticism protects us from inadvertently (or intentionally) misleading stakeholders, which is a massive risk in today's environment.

Supporting Traits

• Trait: Process-Minded
• Desc: You enjoy designing repeatable processes, creating clear documentation, and building systems that make data collection and validation more efficient and less prone to human error. You're always thinking about 'how can we make this easier and more reliable next year?'
• Trait: Adaptable
• Desc: ESG regulations, frameworks, and investor expectations are constantly evolving. You're comfortable with the idea that what we report today might need to change significantly next year, and you can lead your team through that uncertainty without getting flustered.
• Trait: Pragmatic Problem-Solver
• Desc: You understand that perfect data is often a pipe dream, especially for Scope 3 emissions or historical data. You're good at making defensible estimations, documenting your assumptions, and finding 'good enough' solutions when faced with incomplete information, rather than getting stuck chasing perfection.
• Trait: Empathetic Leader
• Desc: You can inspire and guide your team, understanding their challenges in data collection and providing the support and tools they need to succeed. You know when to push and when to protect them from unreasonable demands.

Primary Motivators

1. Motivator: Building Robust Systems
2. Daily: You'll get a real kick out of designing a new data collection workflow in Workiva, integrating a new data source into our reporting platform, or seeing your team successfully implement a new data validation script. The idea of creating something solid and reliable really appeals to you.
3. Motivator: Ensuring Data Integrity & Credibility
4. Daily: The thought of a clean audit report or a strong ESG rating because of the data quality you've overseen will genuinely motivate you. You're driven by the desire to ensure the company's sustainability claims are beyond reproach, knowing your work directly underpins that trust.
5. Motivator: Leading & Developing a Team
6. Daily: You'll enjoy mentoring your direct reports, helping them grow their technical and domain expertise, and watching them take on more complex challenges. Seeing your team thrive and contribute meaningfully will be a significant source of satisfaction.

Potential Demotivators

Honestly, this role isn't for everyone. If you crave absolute control over all data sources, you'll struggle. You'll spend a lot of time chasing data from people who don't report to you, and you'll often have to make difficult calls on data quality when perfect information simply isn't available. You'll also deal with the frustration of constantly changing regulations, meaning processes you built last year might need a significant overhaul this year. If you expect every project to go smoothly without political wrangling or data gaps, you're in for a tough time.

Common Frustrations

1. Inheriting a 'spaghetti junction' of legacy spreadsheets with no documentation for critical historical data.
2. The constant battle to get timely and accurate data from busy operational teams who see ESG as 'extra work'.
3. Having to explain, for the tenth time, why an estimated number for Scope 3 emissions isn't as good as actual primary data.
4. The 'regulation whiplash' of new reporting standards (like CSRD) that require significant rework of established processes.
5. Dealing with subtle (or not-so-subtle) pressure to 'optimise' data to tell a more favourable story, bordering on greenwashing.
6. The low-grade anxiety of an upcoming audit, knowing that one missing piece of data could cause a major headache.

What Role Doesn't Offer

1. A static, predictable environment where processes rarely change.
2. Complete autonomy over all data inputs without needing to influence other departments.
3. A role where you only focus on 'green' initiatives without getting into the nitty-gritty of data validation and compliance.
4. Immediate, tangible results from every single piece of work; some projects are long-term infrastructure builds.

ADHD Positives

1. The constant influx of new data challenges and regulatory changes can be stimulating, preventing boredom.
2. The need to quickly pivot between different data problems and stakeholder requests can suit a dynamic, multi-focused approach.
3. Hyperfocus can be extremely valuable when deep-diving into complex data anomalies or audit trails, ensuring meticulous accuracy.

ADHD Challenges and Accommodations

1. Maintaining consistent, long-term documentation for data lineage can be challenging; using structured templates and automated prompts can help.
2. The repetitive nature of some data validation tasks might be difficult; breaking these into smaller, varied chunks or automating them where possible is key.
3. Managing multiple priorities and stakeholder demands requires strong organisational tools and clear prioritisation frameworks (e.g., daily stand-ups, visual task boards).

Dyslexia Positives

1. Strong conceptual thinking and ability to see the 'big picture' in complex data sets can be a real asset in identifying trends and strategic implications.
2. Excellent verbal communication skills can be used to explain complex data insights to non-technical stakeholders, which is crucial for a manager.
3. Problem-solving through creative, non-linear approaches can lead to innovative solutions for data collection challenges.

Dyslexia Challenges and Accommodations

1. Proofreading detailed reports and data tables can be time-consuming; using grammar/spelling checkers, text-to-speech tools, and peer review is essential.
2. Organising large amounts of textual documentation (e.g., audit trails, methodology notes) might be difficult; visual tools, mind maps, and structured templates can help.
3. Reading dense regulatory texts can be taxing; using AI summarisation tools and collaborating with legal teams for key interpretations can ease the load.

Autism Positives

1. A strong preference for logic, systems, and order is highly beneficial for building robust data governance frameworks and ensuring data integrity.
2. Exceptional attention to detail and pattern recognition can quickly identify inconsistencies or errors in large datasets, which is invaluable for audit readiness.
3. Direct and honest communication style can cut through corporate jargon, leading to clearer data requirements and expectations with stakeholders.

Autism Challenges and Accommodations

1. Navigating nuanced social dynamics when 'patiently persuading' colleagues for data might be challenging; clear communication scripts or structured interaction protocols can assist.
2. Unexpected changes in data requirements or reporting frameworks can be disruptive; clear communication of changes and structured adaptation plans are helpful.
3. Sensory sensitivities in an open-plan office could be an issue; access to quiet workspaces or noise-cancelling headphones can be provided.

Key Responsibilities

Experience Levels Responsibilities

1. Level: ESG Data & Reporting Manager
2. Responsibilities: Set the overall strategy and roadmap for our ESG data collection, validation, and reporting processes, aligning it with evolving regulatory landscapes (e.g., CSRD, TCFD, ISSB) and investor expectations.
3. Lead, mentor, and manage a small team of ESG Data Analysts and Specialists, fostering their development, assigning projects, and ensuring high-quality, timely deliverables.
4. Design, implement, and maintain the core data governance framework for all ESG metrics, ensuring data lineage, audit readiness, and consistent methodologies across the organisation.
5. Oversee the end-to-end production of our annual sustainability report and other key disclosures, working closely with Investor Relations, Legal, and Communications teams.
6. Act as the primary point of contact for external auditors and ESG rating agencies, confidently defending our data methodologies and reported figures.
7. Drive the selection, implementation, and optimisation of ESG data management platforms (e.g., Workiva, OneTrust, dedicated carbon accounting software) to enhance efficiency and accuracy.
8. Develop and deliver training programmes to internal data providers (e.g., in Operations, HR, IT) on ESG data requirements, ensuring they understand their role in the data ecosystem.
9. Supervision: You'll operate with a high degree of autonomy, reporting to the Director of ESG & Sustainability with monthly strategic alignment meetings. Most day-to-day execution and team management will be your responsibility.
10. Decision: You'll have full technical decision authority within your domain, including methodology choices, data platform configurations, and team project prioritisation. You can approve team expenditures up to £20K and make hiring recommendations for your direct reports. Budget decisions above £20K or significant changes to reporting frameworks require consultation with the Director.
11. Success: Success means our ESG data is consistently audit-ready, our reporting cycle is efficient and smooth, and our ESG ratings show continuous improvement. Your team will be high-performing and engaged, and stakeholders will trust the data you present without question. You'll have successfully navigated at least one major external audit with minimal findings.

Decision-Making Authority

• Type: ESG Data Methodology Selection
• Entry: Follows established methodology; escalates any deviations to manager.
• Mid: Proposes methodology for routine data points; consults manager on complex or new areas.
• Senior: Selects and documents methodologies for specific workstreams; consults manager on significant changes or high-risk areas.
• Type: Data Platform Configuration
• Entry: Inputs data into existing platform fields as instructed.
• Mid: Configures routine data collection campaigns and basic reporting templates within existing platforms.
• Senior: Designs and implements complex data models and reporting templates; recommends new platform features.
• Type: External Audit Responses
• Entry: Prepares requested documentation for manager review; does not interact directly with auditors.
• Mid: Responds to routine auditor queries under supervision; prepares documentation for specific data points.
• Senior: Manages specific sections of the audit process; drafts responses to complex queries for manager approval.
• Type: Team Hiring & Performance
• Entry: No involvement.
• Mid: Provides feedback on junior candidates during interviews.
• Senior: Interviews junior candidates; provides input on performance reviews for mentees.

Competency Requirements

Foundation Skills (Transferable)

Beyond the technical skills, a manager in this space needs to be a strong leader and communicator, capable of navigating complex organisational dynamics and driving change. These are the bedrock skills that let you lead a team and influence across departments.

• Category: Communication & Influence
• Skills: Executive Presentation Skills: Clearly and concisely presenting complex ESG data and its implications to senior leadership and the board, often under pressure.
• Cross-functional Collaboration: Building strong working relationships with other department heads (e.g., Finance, IT, Operations, HR) to secure data and drive process improvements.
• Negotiation & Persuasion: Effectively advocating for resources, data requirements, and process changes with stakeholders who may have competing priorities.
• Written Reporting & Storytelling: Crafting compelling, accurate, and auditable narratives for sustainability reports, investor disclosures, and internal communications.
• Category: Problem-Solving & Strategic Thinking
• Skills: Complex Problem Deconstruction: Breaking down ambiguous, multi-faceted ESG data challenges (e.g., Scope 3 calculation for a new product line) into manageable components.
• Root Cause Analysis: Identifying the underlying reasons for data quality issues or reporting bottlenecks, rather than just treating symptoms.
• Strategic Planning & Roadmap Development: Creating a multi-year vision for the ESG data function, anticipating future regulatory changes and technology advancements.
• Risk Management: Identifying and mitigating data-related risks, particularly those pertaining to audit findings, reputational damage, and regulatory non-compliance.
• Category: Leadership & Team Development
• Skills: Performance Management: Setting clear expectations, providing constructive feedback, and conducting regular performance reviews for direct reports.
• Mentorship & Coaching: Guiding and developing junior team members, helping them grow their technical skills and navigate career challenges.
• Conflict Resolution: Mediating disagreements within the team or between the team and other departments regarding data ownership or priorities.
• Change Management: Leading the team through periods of significant change, such as new platform implementations or major regulatory shifts.
• Category: Adaptability & Resilience
• Skills: Navigating Ambiguity: Operating effectively in an environment where regulations are still evolving and perfect data is rare, making sound judgments with incomplete information.
• Pressure Management: Maintaining composure and effectiveness during peak reporting cycles, external audits, or when facing challenging questions from senior stakeholders.
• Continuous Learning: Staying abreast of the latest developments in ESG reporting, data management technologies, and sustainability science.

Functional Skills (Role-Specific Technical)

This role demands a deep understanding of ESG reporting, carbon accounting, and data management best practices, coupled with the technical prowess to implement and oversee the necessary systems. You're not just a data expert; you're an ESG expert.

Technical Competencies

• Skill: ESG Reporting Frameworks (GRI, SASB, TCFD, CSRD, ISSB)
• Desc: You'll need an expert-level understanding of the specific disclosure requirements, metrics, and nuances of all major ESG reporting frameworks. This includes not just knowing what to report, but *why* and *how* to interpret the 'grey areas' and ensure compliance, especially with emerging regulations like CSRD.
• Level: Expert
• Skill: GHG Protocol & Carbon Accounting (Scopes 1, 2, 3)
• Desc: You'll be the ultimate authority on our carbon footprint calculations. This means an expert grasp of the GHG Protocol standards, from direct emissions (Scope 1 & 2) to the complex estimation and data collection strategies for our entire value chain (Scope 3). You'll oversee the methodologies and ensure audit readiness.
• Level: Expert
• Skill: Materiality Assessment (Financial & Double Materiality)
• Desc: You'll lead the process of identifying which ESG issues are most relevant to our business and its stakeholders. This involves understanding both financial materiality (impact on the business) and impact materiality (impact of the business on society/environment), and guiding executive workshops to create our materiality map.
• Level: Advanced
• Skill: Data Validation & Assurance Readiness
• Desc: This is about embedding a culture of audit readiness. You'll design and implement the processes to ensure all ESG data is accurate, well-documented, traceable, and can withstand rigorous scrutiny from third-party auditors. You'll own the 'audit trail' for every reported number.
• Level: Expert
• Skill: ESG Rating Agency Analysis
• Desc: You'll have an advanced understanding of how rating agencies like MSCI, Sustainalytics, and ISS assess companies. This means deconstructing their methodologies, identifying our strengths and weaknesses, and strategically advising on data disclosures to improve our scores.
• Level: Advanced
• Skill: Supply Chain Data Management
• Desc: You'll oversee the complex task of collecting, cleansing, and estimating data from hundreds or thousands of suppliers. This requires strategic thinking around data collection tools, engagement strategies, and robust estimation methodologies for Scope 3 emissions and other supply chain impacts.
• Level: Advanced

Digital Tools

• Tool: ESG Data Platforms (MSCI ESG Research, Sustainalytics, EcoVadis, Refinitiv, Bloomberg)
• Level: Strategic
• Usage: Leading the selection, negotiation, and strategic use of these platforms to gather, benchmark, and report ESG data. You'll be defining how we use these tools to inform strategy and improve ratings, not just pull reports.
• Tool: Reporting & GRC Platforms (Workiva Wdesk, OneTrust ESG, ServiceNow GRC)
• Level: Architect
• Usage: Designing the enterprise-wide ESG data governance framework and reporting workflows within these platforms. You'll oversee the build of complex data models, assurance workflows, and audit trails to ensure compliance and efficiency.
• Tool: Data Analysis (Python - pandas, SQL)
• Level: Advanced
• Usage: Overseeing and guiding your team in using Python (especially pandas) and SQL for complex data cleaning, transformation, and analysis of large, unstructured ESG datasets. You'll set the standards for scripting and data integrity.
• Tool: Data Visualization (Power BI/Tableau)
• Level: Strategic
• Usage: Defining the executive visualization strategy for ESG data. You'll ensure dashboards are impactful, tell a clear story, and provide actionable insights for board-level reporting and internal decision-making.
• Tool: Collaboration & Documentation (Confluence, Notion, Jira)
• Level: Advanced
• Usage: Establishing and enforcing best practices for documenting data methodologies, creating data dictionaries, and managing project knowledge bases. You'll ensure all team work is transparent and auditable.
• Tool: ERP/HRIS Systems (SAP S/4HANA, Oracle HCM, Workday HCM)
• Level: Architect
• Usage: Influencing the configuration and data capture capabilities of these core enterprise systems to ensure they effectively support ESG data requirements. You'll work with IT to define requirements for custom extracts and integrations.

Industry Knowledge

• Area: Global Sustainability Trends & Policy
• Desc: A deep understanding of major global sustainability trends, climate science, biodiversity loss, social equity issues, and how these translate into business risks and opportunities. You'll need to anticipate future policy directions.
• Area: Investor Expectations on ESG
• Desc: Knowledge of what institutional investors, proxy advisors, and activist shareholders are looking for in ESG disclosures, and how to effectively communicate our performance to them.
• Area: Corporate Governance Best Practices
• Desc: Understanding of effective board oversight of sustainability, executive compensation links to ESG, and shareholder engagement on ESG topics.

Regulatory Compliance Regulations

• Reg: Corporate Sustainability Reporting Directive (CSRD) / European Sustainability Reporting Standards (ESRS)
• Usage: You'll be responsible for ensuring our company's full compliance with CSRD, overseeing the double materiality assessment, data collection against ESRS, and the preparation of the management report. This is a critical piece of your role.
• Reg: Task Force on Climate-related Financial Disclosures (TCFD)
• Usage: You'll ensure our climate-related financial disclosures meet TCFD recommendations, covering governance, strategy, risk management, metrics, and targets. This often involves working closely with Finance and Risk teams.
• Reg: SEC Climate Disclosure Rules (Proposed)
• Usage: You'll need to track and prepare for potential SEC climate disclosure requirements, understanding their implications for our US operations and reporting, and ensuring our data systems can support them if enacted.
• Reg: UK Green Taxonomy & SDR
• Usage: Understanding the UK's sustainable finance regulations, including the Green Taxonomy and Sustainability Disclosure Requirements, and ensuring our reporting aligns where applicable.

Essential Prerequisites

• Proven experience (at least 5-8 years) leading ESG data collection and reporting processes, ideally in a large, complex organisation or a consultancy advising such clients.
• Demonstrable expertise in at least two major ESG reporting frameworks (e.g., GRI, SASB, TCFD, CSRD).
• Strong experience with carbon accounting principles (GHG Protocol Scope 1, 2, 3) and associated data challenges.
• Experience managing and mentoring junior data professionals, including setting objectives and providing performance feedback.
• Hands-on experience with at least one enterprise-level ESG reporting or GRC platform (e.g., Workiva, OneTrust, ServiceNow GRC) beyond basic data entry.
• A solid understanding of data governance principles, including data quality, lineage, and audit trails.
• Excellent communication skills, both written and verbal, with a track record of presenting complex information to senior audiences.

Career Pathway Context

Typically, candidates for this role would have spent several years as a Senior ESG Data Analyst or an ESG Reporting Specialist, having 'owned' specific frameworks or complex data streams. They'll have a proven track record of improving data quality and streamlining reporting processes before stepping into a management role.

Qualifications & Credentials

Emerging Foundation Skills

• Skill: AI-Powered Data Governance & Assurance
• Why: With the explosion of ESG data and the increasing scrutiny from regulators and auditors, manually ensuring data quality and audit readiness for every single data point is becoming impossible. AI will be crucial for scaling data governance, flagging anomalies, and automating assurance processes.
• Concepts: [{'concept_name': 'Machine Learning for Anomaly Detection', 'description': 'Using ML models to automatically identify unusual patterns or outliers in large ESG datasets that might indicate errors or fraud.'}, {'concept_name': 'Natural Language Processing (NLP) for Source Document Verification', 'description': 'Applying NLP to automatically scan and extract data from unstructured documents (e.g., supplier contracts, utility bills) and verify against reported figures.'}, {'concept_name': 'AI-driven Data Lineage Mapping', 'description': 'Tools that can automatically map the journey of a data point from its source to its final report, creating an auditable trail without manual effort.'}, {'concept_name': 'Predictive Compliance Monitoring', 'description': 'Using AI to anticipate future regulatory changes and assess their potential impact on our data collection and reporting requirements.'}]
• Prepare: This quarter: Research and pilot an AI-powered data quality tool (e.g., within Workiva or a standalone solution) for a specific ESG dataset.
• Next 6 months: Work with the IT and Data Governance teams to explore integrating AI into our broader data governance strategy.
• Next 12 months: Develop a strategy for how AI can enhance our internal audit readiness processes, focusing on automated verification.
• Continuously: Stay informed on new AI solutions specifically designed for ESG data management and assurance; attend webinars and industry events.
• QuickWin: Start experimenting with AI tools (like advanced Excel add-ins or Python libraries) for simple anomaly detection in your current datasets. No need for a big project, just get hands-on.
• Skill: Integrated Reporting (Financial & ESG)
• Why: Regulators (like the ISSB) are pushing for greater convergence between financial and sustainability reporting. As a manager, you'll need to lead this integration, ensuring ESG data is treated with the same rigour as financial data and is seamlessly incorporated into our broader corporate disclosures.
• Concepts: [{'concept_name': 'International Sustainability Standards Board (ISSB) Standards', 'description': 'Understanding the IFRS S1 and S2 standards and their implications for financial reporting of sustainability-related information.'}, {'concept_name': 'Financial Materiality vs. Double Materiality', 'description': 'Distinguishing between these concepts and applying them correctly in integrated reporting contexts.'}, {'concept_name': 'Interoperability of Reporting Frameworks', 'description': 'How to map and align data points across different frameworks (e.g., GRI, SASB, TCFD, ISSB) to create a cohesive report.'}, {'concept_name': 'Assurance for Integrated Reports', 'description': 'Understanding the requirements for obtaining assurance over both financial and sustainability information in a single report.'}]
• Prepare: This quarter: Deep dive into the ISSB standards and their implications for our current reporting structure; identify key gaps.
• Next 6 months: Work closely with the Finance team to understand their reporting processes and identify opportunities for data integration.
• Next 12 months: Develop a phased roadmap for integrating key ESG metrics into our financial reporting systems and processes.
• Continuously: Participate in industry working groups or conferences focused on integrated reporting and financial-ESG convergence.
• QuickWin: Start by identifying 2-3 key ESG metrics that have a direct financial impact (e.g., carbon price exposure, water scarcity risk) and work with Finance to include them in internal risk assessments or management dashboards.

Advancing Technical Skills

• Skill: Advanced Data Orchestration & Pipelines
• Why: As ESG data sources proliferate (IoT sensors, satellite imagery, external databases), the ability to build robust, automated data pipelines that ingest, transform, and load data reliably will be critical. Manual processes won't scale.
• Concepts: [{'concept_name': 'ETL/ELT Frameworks (e.g., Apache Airflow, Azure Data Factory)', 'description': 'Understanding how to design and manage automated data workflows for complex ESG datasets.'}, {'concept_name': 'Cloud Data Warehousing (e.g., Snowflake, Azure Synapse)', 'description': 'Strategic understanding of how to store and manage vast amounts of ESG data in scalable cloud environments.'}, {'concept_name': 'API Integration for Data Sources', 'description': 'Connecting directly to external data providers or internal systems via APIs for real-time or near real-time data ingestion.'}, {'concept_name': 'Data Governance in Automated Pipelines', 'description': 'Ensuring data quality checks, validation, and audit logging are built directly into automated data flows.'}]
• Prepare: This quarter: Work with your IT team to understand our current enterprise data architecture and identify opportunities for ESG data integration.
• Next 6 months: Oversee a project to automate a key ESG data pipeline using an ETL tool or cloud service, even if your team doesn't build it directly.
• Next 12 months: Develop a long-term strategy for integrating all material ESG data into our central data warehouse, ensuring scalability and accessibility.
• Continuously: Stay updated on new data engineering tools and best practices, particularly those relevant to unstructured and diverse data types.
• QuickWin: Identify one highly manual, repetitive data collection process and explore how a simple API integration or low-code ETL tool could automate a significant portion of it. Start small, prove the concept.

Education Requirements

• Level: Minimum
• Req: A Bachelor's degree in a relevant field such as Environmental Science, Sustainability, Data Science, Finance, Business Administration, or a related quantitative discipline.
• Alts: We're pragmatic. If you've got equivalent professional experience (roughly 12-16 years in a similar senior data or reporting role, with a strong focus on ESG), we're absolutely open to that. Show us what you can do.
• Level: Preferred
• Req: A Master's degree in Sustainability Management, Environmental Engineering, Data Analytics, or an MBA with a specialisation in ESG.
• Alts: Relevant certifications and extensive practical experience often outweigh a specific postgraduate degree. It's about what you know and how you apply it.

Experience Requirements

You'll need roughly 12-16 years of progressive experience in data management, reporting, or sustainability roles, with a significant portion (at least 5-8 years) directly focused on ESG data and reporting. This should include at least 3-5 years in a leadership or management capacity, overseeing data processes and ideally managing a small team. We're looking for someone who has 'been there, done that' when it comes to navigating complex reporting cycles and external audits.

Preferred Certifications

• Cert: SASB FSA Credential (Fundamentals of Sustainability Accounting)
• Prod: IFRS Foundation
• Usage: Demonstrates a solid understanding of financially material sustainability information and how it's used in reporting and investment decisions.
• Cert: GRI Certified Sustainability Professional
• Prod: Global Reporting Initiative (GRI)
• Usage: Shows deep expertise in applying the widely used GRI Standards for comprehensive sustainability reporting.
• Cert: Certified ESG Analyst (CESGA)
• Prod: EFFAS (European Federation of Financial Analysts Societies)
• Usage: A strong credential for understanding ESG integration in financial analysis and investment processes, which is key for investor relations.
• Cert: Project Management Professional (PMP) or PRINCE2
• Prod: PMI / AXELOS
• Usage: Valuable for managing complex reporting projects, platform implementations, and leading cross-functional initiatives efficiently.

Recommended Activities

• Regularly attending industry conferences and webinars on ESG reporting, data governance, and sustainable finance (e.g., GreenFin, Responsible Business Summit).
• Participating in professional networks or working groups focused on specific ESG topics or reporting frameworks.
• Subscribing to key regulatory updates and thought leadership from organisations like the IFRS Foundation, GRI, and major consultancies.
• Engaging in continuous learning around new data management tools, AI applications, and cloud technologies relevant to ESG data.

Career Progression Pathways

Entry Paths to This Role

• Path: Senior ESG Data Analyst / ESG Reporting Specialist (L3-L4)
• Time: 5-8 years experience
• Path: Sustainability Consultant (with data focus)
• Time: 8-12 years experience
• Path: Data Governance Manager (with ESG exposure)
• Time: 10-14 years experience

Career Progression From This Role

• Pathway: Director of ESG & Sustainability (L6)
• Time: 3-5 years in current role

Long Term Vision Potential Roles

• Title: Chief Sustainability Officer (CSO) (L7)
• Time: 8-12+ years from this role
• Title: Head of Investor Relations (with ESG focus)
• Time: 5-8 years from this role
• Title: Head of Data Governance & Analytics (Enterprise-wide)
• Time: 6-10 years from this role

How Zavmo Delivers This Role's Development

DISCOVER Phase: Skills Gap Analysis

Zavmo maps your current competencies against all requirements in this job description through conversational assessment. We evaluate your foundation skills (communication, strategic thinking), functional skills (CRM expertise, negotiation), and readiness for career progression.

Output: Personalised skills gap heat map showing strengths and priorities, estimated time to competency, neurodiversity accommodations.

DISCUSS Phase: Personalised Learning Pathway

Based on your DISCOVER results, Zavmo creates a personalised learning plan prioritised by impact: foundation skills first, then functional skills. We adapt to your learning style, pace, and neurodiversity needs (ADHD, dyslexia, autism).

Output: Week-by-week schedule, each module linked to specific job responsibilities, checkpoints and milestones.

DELIVER Phase: Conversational Learning

Learn through conversation, not boring modules. Zavmo uses 10 conversation types (Socratic dialogue, role-play, coaching, case studies) to build competence. Practice difficult QBR presentations, negotiate tough renewals, and handle churn conversations in a safe AI environment before facing real clients.

Example: "For 'Stakeholder Mapping', Zavmo will guide you through analysing a complex enterprise account, identifying key decision-makers, and building an engagement strategy."

DEMONSTRATE Phase: Competency Assessment

Zavmo automatically builds your evidence portfolio as you learn. Every conversation, practice scenario, and application example is captured and mapped to NOS performance criteria. When ready, your portfolio supports OFQUAL qualification claims and demonstrates competence to employers.

Output: Competency matrix, evidence portfolio (downloadable), qualification readiness, career progression score.