UK

United Kingdom · Sustainability · Lead (8-12 years)

Lead ESG Performance Manager

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  • Experience bandLead (8-12 years)
  • Direct reports3-5 reports
  • Reports toESG Reporting & Performance Manager
  • UK framework levelUsually a manager, or the deepest specialist in a team

Also advertised as Principal Sustainability Data Architect · Senior ESG Reporting Lead · Head of ESG Data & Assurance · Sustainability Programme Lead

Built on 43,079 real UK job descriptions we analysed · grounded in what real qualifications cover

Two short quizzes about you

1From this job to a course

The qualifications matched to this job

NCC Education Level 5 Extended Diploma in Computing with Data Science NCC Education Limited · Level 5 · covers 1 of 5 standards
Level 6 Award in Data-led Decision Making Institute of Sales Professionals · Level 6 · covers 1 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Computing for England Pearson Education Ltd · Level 5 · covers 1 of 5 standards
Pearson BTEC Level 5 Higher National Diploma in Digital Technologies Pearson Education Ltd · Level 5 · covers 1 of 5 standards
Level 6 Certificate in Professional Sales Institute of Sales Professionals · Level 6 · covers 1 of 5 standards

Matched from the standards this job is measured against: a suggestion, not an official ruling.

The units you would start with

Introduction to Data Science and Big Data NCC Education Level 5 Extended Diploma in Computing with Data Science
Data-led Decision Making Level 6 Award in Data-led Decision Making
Apply the Concepts of Data Science to Computer Engineering NOCN Level 5 Diploma in Computer Engineering (Information Technology and Data Science)
Data Analytics Pearson BTEC Level 5 Higher National Diploma in Computing for England

The future skills this job leans on

AI Fluency working with AI as a thinking partner
Data Fluency turning numbers into a decision
AI Governance Fluency using AI responsibly
Sustainability Fluency building care for people and planet into the work
Systems Fluency seeing the whole picture
Your Plan Illustration

Built for Lead ESG Performance Manager

4 units that map to this job, from the qualifications that cover it.

  1. Introduction to Data Science and Big Data NCC Education Limited · covers 1 of 5 standards Level 5
  2. Data-led Decision Making Institute of Sales Professionals · covers 1 of 5 standards Level 6
  3. Apply the Concepts of Data Science to Computer Engineering NOCN · covers 1 of 5 standards Level 5
  4. Data Analytics Pearson Education Ltd · covers 1 of 5 standards Level 5
These are the real units behind this job, in the order they rank for it. Nothing here is marked done, because this plan has not been started by anyone yet. Yours would fill in as you go.

2AI and this work

Will AI change your work as a Lead ESG Performance Manager?

Nobody can say exactly how. Here is what this job is being asked for next, and where to start.

The new skills this role is being asked for

  • Prompt Engineering & LLM Integration for ESG
  • Data Storytelling & Visualisation for Impact
Why each one is rising

The future skills this job leans on

We'll only ever tell you what we can actually back up. No hype, no scare tactics.

What happens when you start

Next, a free account. We build your Lead ESG Performance Manager plan as you set up, starting with the free Automation Fluency module. No card.

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Keep this read. One email with what AI is changing in this job, the new skills it asks for and where to start free. Nothing else follows unless you confirm your address.

3What this role really is

A Lead ESG Performance Manager measures and reports on environmental, social and governance performance for an organisation. You build the data collection systems behind ESG reporting and make sure the numbers hold up to scrutiny. This work drives how an organisation understands and reports its sustainability performance.

4What you'd actually use

The tools this job runs on, and how well you'd need to know each one.

ESG Data Platforms (e.g., Workiva, OneTrust, Sphera, Enablon) Expert

You'll be configuring data collection templates, building custom dashboards, managing user permissions, and troubleshooting integration issues. You'll also train business users on how to use these platforms effectively. You might even lead the selection process for new modules or platforms.

BI & Analytics (e.g., Power BI, Tableau) Advanced

Connecting to various data sources (SQL, Excel, ESG platforms), building complex, multi-page dashboards for internal and external reporting, and using advanced functions (like DAX in Power BI) to create new metrics and visualisations. You'll be presenting these to senior leaders.

Spreadsheets (e.g., Excel, Google Sheets) Expert

Mastering Power Query for ETL (Extract, Transform, Load) operations, building and auditing complex carbon or financial models, and potentially writing simple VBA macros to automate repetitive tasks. You'll also design spreadsheet-based data collection systems for parts of the business that lack formal tools.

GRC & Reporting (e.g., Diligent, Workiva for reporting, ServiceNow GRC) Advanced

Mapping ESG controls to identified risks, drafting and reviewing narrative content within reporting platforms, and managing the internal review and approval workflows for the annual sustainability report. You'll ensure technology supports regulatory requirements like CSRD XBRL tagging.

Data Querying (e.g., SQL) Intermediate

Writing basic to intermediate `SELECT...FROM...WHERE` queries to pull raw data from corporate data warehouses (e.g., operational energy consumption, HR data) for analysis and integration into ESG systems. You'll work with IT to define data requirements.

5What you get to decide, and how that grows

Power in a job isn't your title. It's what you're allowed to decide. Here's how it grows as you move up.

The choiceComing in Where you are nowThe step above
ESG Data Collection Methodology Follows established methodology; escalates any deviations. Adapts established methodology for specific cases; proposes minor improvements. Designs and implements new methodologies for complex data streams; consults on strategic implications.
Process Improvement Implementation Identifies minor inefficiencies; proposes solutions to supervisor. Implements approved process improvements for own workstream. Designs and leads implementation of significant process improvements across multiple workstreams or for the entire data collection cycle. Approves changes up to £10K.
External Auditor Engagement Prepares requested documentation under supervision. Responds to routine auditor queries; prepares sections of audit evidence. Leads the coordination of external ESG audits; addresses complex auditor questions; directly manages evidence provision and follow-up actions.
Team Work Allocation & Prioritisation Receives assigned tasks; prioritises daily work based on guidance. Manages own project tasks; helps prioritise for specific initiatives. Allocates tasks and prioritises work for direct reports (3-5 people); balances team workload against programme deadlines. Makes resource recommendations for larger projects.

6How you'll be judged

The scoreboard, and what is not on it. The hard targets, how often each is actually looked at, and the quiet signals that never reach a dashboard.

Data Assurance Readiness Score
The percentage of key ESG data points (e.g., Scope 1 & 2 emissions, water withdrawal) that are fully documented and auditable according to our internal assurance protocols.
Target · Achieve 90% assurance readiness for all material ESG data points.

If we have 100 material data points, 90 of them should have complete, traceable documentation ready for an auditor at any time. This means clear source documents, calculation methodologies, and sign-offs.

Reduction in External Audit Findings
The year-over-year decrease in the number of material weaknesses or significant deficiencies identified by our external ESG auditors related to data quality or process.
Target · Reduce audit findings by 50% compared to the previous year.

Last year, auditors found 4 significant issues with our GHG data collection. This year, your goal is to get that down to 2 or fewer by fixing processes and improving data quality.

ESG Data System Uptime & Reliability
The percentage of time our core ESG data collection and reporting platforms (e.g., Workiva, internal dashboards) are operational and providing accurate data.
Target · Maintain 99.5% uptime for critical ESG data systems.

If a key data platform goes down for more than 4 hours in a month, or consistently provides incorrect data, that impacts this metric. We need these systems to be dependable.

Team Productivity (Data Processing Efficiency)
The average time it takes your team to process and validate a standard data set (e.g., a month's worth of utility bills for a site) from raw input to 'assurance-ready' status.
Target · Reduce average data processing time by 20% through process improvements and automation.

If it currently takes an analyst 8 hours to process a specific data set, your goal is to get that down to 6.4 hours by streamlining steps or introducing new tools.

Stakeholder Confidence in ESG Data
How much internal and external stakeholders (e.g., Finance, Operations, external auditors) trust the accuracy and robustness of our reported ESG data.
  • You'll know you're doing well if Finance stops double-checking your numbers before board reports, if operational managers proactively offer data, and if external auditors comment positively on the quality of your documentation. We'll also look at feedback from investor calls where ESG data is discussed.
Process Innovation & Improvement
Your ability to identify bottlenecks, design better data collection workflows, and implement new technologies or methodologies to improve efficiency and data quality.
  • This shows up as new, streamlined processes being adopted across the business, fewer manual workarounds, and positive feedback from your team and data providers about how much easier it is to submit or access data. You'll be presenting ideas for improvement and seeing them through.
Mentorship & Team Development
How effectively you guide and develop the ESG analysts and specialists on your team, helping them grow their skills and take on more complex responsibilities.
  • You'll see your team members successfully owning more complex data streams, proposing solutions to problems, and feeling supported in their learning. We'll check in with your direct reports during their performance reviews to get their perspective on your mentorship.
Regulatory Foresight
Your ability to anticipate upcoming regulatory changes (e.g., new CSRD requirements) and proactively adapt our data collection and reporting systems to meet them before they become urgent problems.
  • This means presenting clear plans for new regulations well in advance, having systems ready for new data points before they're legally required, and avoiding last-minute scrambles when new rules come into force. You're not just reacting, you're planning ahead.

7Would you like it

Both sides. What people enjoy, and what grinds them down.

What people enjoy
Building Robust Systems

You'll get a real kick out of designing a new data collection template that actually works, or seeing a complex data flow you architected run smoothly. It's about creating order and efficiency where there was once chaos.

Successfully implementing a new Workiva module that automates 30% of our manual data entry for GHG emissions, meaning fewer errors and less time spent chasing numbers.

Ensuring Data Integrity & Credibility

You'll feel a strong sense of satisfaction when an external auditor signs off on your work with minimal findings, or when a senior leader praises the clarity and accuracy of your data. It's about being the guardian of truth.

Receiving positive feedback from the Board's Audit Committee on the robustness of our ESG data governance framework, directly attributable to your designs.

Shaping Strategic Decisions with Data

While you're deep in the data, you'll know that the numbers you're producing are directly informing our company's sustainability strategy, investment decisions, and public commitments. You're not just reporting; you're influencing.

Seeing a new decarbonisation target set by the executive team, knowing it was based on the detailed Scope 3 emissions analysis and reduction pathways you modelled and presented.

What frustrates people
  • The Data Janitor Reality: Expect to spend a significant chunk of your time (sometimes 50%+) chasing, cleaning, and validating data from a patchwork of spreadsheets, PDFs, and legacy operational systems, not just on high-level strategy.
  • Responsibility without Authority: You're accountable for the accuracy of the corporate carbon footprint, but you have zero direct authority over the factory managers or procurement teams who actually control those emissions. It's all about influence.
  • Regulation Whiplash: Just when you've perfected your reporting process for one framework (e.g., GRI), a new one (like CSRD) comes along and forces a complete redesign of your data collection and governance. It's a constant moving target.
  • The Annual Report Fire Drill: Despite a year-long plan, the final two months before the sustainability report is published will inevitably become a chaotic scramble of late data, last-minute executive reviews, and late nights. It's just the nature of the beast.
  • Explaining It. Again.: You will find yourself explaining the difference between market-based and location-based Scope 2 emissions to the same senior leaders every single quarter. Patience is key.
What this role does not give you
  • A purely strategic role with no hands-on data work.
  • A predictable, unchanging set of tasks or regulations.
  • Direct authority over operational teams or budgets outside your function.
  • A role where you don't have to deal with messy, incomplete data.

8Who you work with

This role directly underpins the credibility and integrity of our entire corporate sustainability disclosure. You're building the data infrastructure that allows us to set meaningful targets, track progress, and communicate our impact to the world. Get it right, and we enhance our reputation and attract responsible investment. Get it wrong, and we face significant reputational and financial risks.

Inside the business
  • ESG Reporting & Performance Manager (your direct boss)
  • Head of Sustainability
  • Finance (especially for carbon pricing and financial materiality)
  • Operations (for energy, water, waste data)
  • HR (for diversity, equity, and inclusion metrics)
  • Legal (for regulatory compliance and report review)
  • Internal Audit team
Outside the business
  • External ESG Auditors (e.g., Big Four firms)
  • ESG Rating Agencies (MSCI, Sustainalytics, CDP)
  • Key Institutional Investors
  • Industry bodies and working groups

9What you need before you start

Not a wish list. The things you would be expected to already have.

  • At least 8 years of dedicated experience in ESG data management, sustainability reporting, or a closely related field (e.g., financial reporting with a strong ESG component).
  • Demonstrable experience in designing and implementing data collection processes for complex, auditable data sets.
  • Proven track record of leading external assurance processes for sustainability reports or similar disclosures.
  • Experience in managing or technically mentoring a small team of analysts or specialists.
  • A deep, practical understanding of major ESG reporting frameworks (GRI, SASB, TCFD, ESRS) and carbon accounting (GHG Protocol).
  • Advanced proficiency with at least one major ESG data platform (e.g., Workiva, OneTrust) and strong BI dashboarding skills (e.g., Power BI, Tableau).

10What to practise next

Where the job is going, and what to do about it starting this week.

Advanced Data Modelling & Predictive Analytics

Regulators and investors are increasingly asking for forward-looking ESG data, like scenario analysis for climate risk or predictive models for social impact. We need to move beyond just reporting what happened to forecasting what might happen.

Regression analysis for impact drivers · Time series forecasting for ESG metrics · Climate scenario analysis (e.g., TCFD) · Monte Carlo simulations for risk assessment · Ethical considerations in predictive modelling

  • This week: Explore online courses on advanced Excel modelling or Python for data science (e.g., with pandas, scikit-learn).
  • This month: Build a simple predictive model for one of our internal ESG metrics (e.g., predicting next year's waste generation).
  • Month 2: Research and apply a basic climate scenario analysis framework to a specific part of our business.
  • Month 3: Present your model's findings and limitations to your manager, discussing how it could inform strategy.

Quick win: Start experimenting with Excel's 'Forecast Sheet' function on some of our historical ESG data to get a feel for predictive analysis. It's built-in and easy to use.

API Integration & Data Pipeline Automation

Manual data collection is slow, error-prone, and unsustainable. As we scale, we need to automate the flow of data from source systems (ERP, HRIS, IoT sensors) directly into our ESG platforms and BI tools. This requires understanding APIs and data pipelines.

RESTful APIs for data exchange · ETL (Extract, Transform, Load) processes · Data warehousing concepts · Cloud data platforms (e.g., Azure Data Factory, AWS Glue) · Data security and privacy in pipelines

  • This week: Research common APIs used in our industry (e.g., for energy monitoring, HR systems).
  • This month: Take an online course on Python for API interactions or an introduction to cloud data engineering.
  • Month 2: Work with our IT team to map out the data flow from one key operational system to our ESG platform, identifying automation opportunities.
  • Month 3: Develop a proof-of-concept script to pull data from a simple API and integrate it into a spreadsheet or internal database.

Quick win: Identify one small, repetitive data transfer task you do weekly. Research if the source system has an API and how you might automate just that single step. Even a partial automation is a win.

11Staying current once you are in

What people here do to keep up
  • Regularly attending webinars and conferences on new ESG regulations (e.g., CSRD implementation, IFRS S1/S2 updates) and data management best practices.
  • Participating in industry working groups or professional networks focused on sustainability reporting or data assurance.
  • Taking advanced courses in data analytics, Python for data science, or cloud-based data engineering to enhance your technical capabilities.
  • Seeking out mentorship from experienced sustainability professionals or data governance experts within our organisation or externally.

12The rising capability

The rising capability

Zavmo analysis

What's rising in its place

This is where the work is heading, and the higher pay with it. Get fluent here and the shift stops being a threat and starts being your edge.

Prompt Engineering & LLM Integration for ESG

Competitors are already using Large Language Models (LLMs) to draft sections of their sustainability reports in minutes, or to summarise vast amounts of regulatory text. Analysts who master this will outproduce their peers significantly. It's about working smarter, not harder.

  • Context windows and token limits
  • Temperature settings for different tasks
  • RAG (Retrieval-Augmented Generation) architectures
  • Output validation and hallucination detection
  • Prompt chaining for complex analysis

Data Storytelling & Visualisation for Impact

With the sheer volume of ESG data, simply presenting numbers isn't enough. You need to be able to craft compelling narratives and visualisations that resonate with diverse audiences, from the Board to external stakeholders. It's about making the data meaningful and actionable.

  • Audience-centric communication
  • Narrative structure for data
  • Effective chart selection & design
  • Interactive dashboards for exploration
  • Ethical data visualisation

13What you’ll use

What you’ll use

Skills this role draws on

Technical

  • ESG Reporting Frameworks (GRI, SASB, TCFD, ESRS)
  • Materiality Assessment (Double Materiality)
  • GHG Protocol & Carbon Accounting
  • ESG Ratings & Index Analysis
  • Data Governance & Quality Management

14The pathway

The pathway

How you actually get there, here

How you become one varies far more by country than what one does. This is the UK route. Most people take one of these ways in; the right one depends on where you're starting from.

  1. 1

    Senior ESG Performance Specialist

    3-5 years in a Senior role

    Skills to master

    • Leading complex projects (e.g., TCFD scenario analysis), designing process improvements, mentoring junior analysts, and managing significant workstreams independently.

    You're ready to move on when

    • Consistently delivering high-quality, auditable data for complex ESG domains.
    • Successfully leading cross-functional projects with minimal supervision.
    • Proactively identifying and resolving process bottlenecks.
    • Demonstrating strong mentorship capabilities for junior team members.
    • Being the 'go-to' person for technical questions in specific ESG areas.
  2. 2

    ESG Data Consultant (from external firms)

    8-10 years in consulting

    Skills to master

    • Deep experience in implementing ESG reporting frameworks for multiple clients, designing data governance structures, and managing client relationships. You'd be bringing that external best practice knowledge in-house.

    You're ready to move on when

    • Proven experience in end-to-end ESG reporting project delivery for diverse clients.
    • Strong understanding of various industry-specific ESG challenges and solutions.
    • Excellent stakeholder management and client-facing communication skills.
    • Ability to quickly adapt to new organisational structures and internal politics.
  3. 3

    Senior Data Analyst/Scientist (with ESG specialisation)

    8-12 years in data roles

    Skills to master

    • Advanced data modelling, strong programming skills (Python/R), experience with large datasets, and a demonstrated interest or experience in applying these skills to environmental or social data problems.

    You're ready to move on when

    • Expertise in building and maintaining robust data pipelines and analytics solutions.
    • Proven ability to translate complex data into actionable insights.
    • A clear passion for sustainability and understanding of ESG data nuances.
    • Experience working with diverse data sources and ensuring data quality.

15Where this role leads

The long view: This role can lead into sustainability leadership or into broader data governance and risk work. It can also open the way to consulting, ratings work, or sustainable finance roles.

The ten Future Fluencies

Zavmo analysis

The credential is what you can do today. These are what keep you valuable.

A qualification proves you can do the job as it's defined today. These ten are what decide whether you're still the obvious person for it in five years. They're the capabilities employers are now writing into senior roles faster than people are learning them. Zavmo weaves them through whatever you study, so you come out with both: the credential and the fluency.

The highlighted ones are the Fluencies your role leans on hardest, from how Lead ESG Performance Manager is actually changing.

Where it leads

Roles this leads to

Also named as a next step, with no page in the catalogue yet:

  • Principal ESG Data Architect (Individual Contributor)

How you would learn this

One to one, on the work you already do

A tutor sets the task against your own job and marks the reasoning, at your pace. There is no cohort to fall behind.

A lesson from Introduction to Data Science and Big Data, worked against Lead ESG Performance Manager.

Introduction to Data Science and Big Data Level 5

Applied to your work in Lead ESG Performance Manager

The objective of this unit is to provide learners with a systematic understanding of Data Science and Big Data concepts, including their characteristics and applications. Learners will develop proficiency in data collection, design, and modelling techniques, and will be able to select appropriate tools for data pre-processing and apply analytical techniques to generate insights from data.

How the thinking builds
  1. 1 Remember
  2. 2 Understand
  3. 3 Apply
  4. 4 Analyse
  5. 5 Evaluate
  6. 6 Create
An illustration of a Zavmo lesson, built from this role’s own route. The unit, its objective and every criterion above are the awarding body’s own words, not an example.

It is £70 a month, billed monthly. Your free first module is Future Fluency, and you can cancel any time.

See Your Progress Grow Illustration
Lead ESG Performance Manager
  • ESG Reporting Frameworks (GRI, SASB, TCFD, ESRS)
  • Materiality Assessment (Double Materiality)
  • GHG Protocol & Carbon Accounting
  • ESG Ratings & Index Analysis
  • Data Governance & Quality Management
This is your Mind Palace on learn.zavmo.ai. Every skill above comes from this role's own record, not an example borrowed from another job. A node lights up when you evidence it, and what you build stays yours between jobs. That is the part a course cannot do.

16The detail, folded away

Everything else the record holds

The career branches in full, how AI is already showing up in the day-to-day, and the questions people ask about this job. Here when you want them, out of the way while you decide.

Where it leads next, rung by rung

Where it leads

The career path, and where it branches

Lead ESG Performance Manager is a start, not a ceiling. Each step below asks for new skills and hands back more autonomy.

  1. ESG Reporting & Performance Manager (Level 005)

    3-5 years

    You'd move from architecting specific domains to managing the entire ESG reporting cycle and leading a larger team (including other Lead Managers). This role owns the overall functional goals and interfaces with Director-level stakeholders.

    • Organisational Design for ESG Structuring the ESG performance function to maximise efficiency and impact.
    • External Representation Representing the organisation in key industry forums or with major investor groups on reporting matters.
    • Advanced Risk Management Integrating ESG data risks into broader enterprise risk management frameworks.
    • P&L Acumen Understanding the financial implications of ESG performance and reporting on the company's P&L.

  2. Principal ESG Data Architect (Individual Contributor)

    3-5 years

    This is a non-managerial path, focusing on deep technical expertise. You'd become the ultimate technical authority on ESG data architecture, designing enterprise-wide solutions and advising on the most complex data challenges across the business. Your scope would be broader, but without direct reports.

    • Cloud Data Engineering Expertise in building and managing scalable data pipelines and warehouses in cloud environments (e.g., Azure, AWS, GCP).
    • Data Security & Privacy (Advanced) Deep knowledge of data protection regulations and best practices for securing sensitive ESG data.
    • Advanced Analytics & Machine Learning Applying sophisticated analytical techniques to extract deeper insights and build predictive models from ESG data.
    • Cross-Domain Integration Designing data solutions that bridge ESG data with financial, operational, and HR data systems.
Working with AI on the job

Working with AI

Where AI is starting to help

Let's be real, a big chunk of ESG performance management is about sifting through data, checking numbers, and drafting reports. What if you could offload a significant portion of that to AI? We're not talking about replacing you, but about giving you a serious superpower.

Our AI Productivity Hub is designed specifically for roles like yours. It's a curated set of tools and best practices that helps you automate the tedious, repetitive parts of ESG data management, freeing you up for the strategic thinking and complex problem-solving that only a human can do. Think of it as having a highly efficient, tireless assistant.

Automated Data Extraction

Use AI-powered OCR to automatically pull key figures and details from unstructured documents like utility bills, waste invoices, and supplier compliance certificates. It populates your spreadsheets or ESG platforms and flags any anomalies, saving you hours of manual entry and cross-referencing.

Anomaly Detection & Insights

Point an AI tool at your time-series data (e.g., monthly energy use per site, employee turnover rates) to automatically flag statistical outliers. This helps you spot potential data errors, meter failures, or operational issues long before a human would, making your data 'assurance-ready' much faster.

Regulatory & Peer Monitoring

Set up an AI agent to continuously scan for and summarise new ESG regulations (like updates to CSRD or TCFD), changes to reporting standards, and the latest sustainability reports from key competitors. You'll get a curated weekly digest, keeping you ahead of the curve without endless manual research.

First-Draft Narrative Generation

Feed your structured data (metrics, targets, performance against KPIs) into a generative AI model to create a solid first draft of the narrative for sections of your annual sustainability report. This gives you a strong starting point that you can then refine, add nuance to, and ensure it aligns with our brand voice, cutting down drafting time significantly.

Common questions

Common questions

How do you become a Lead ESG Performance Manager?

Common routes in include Senior ESG Performance Specialist (3-5 years in a Senior role), ESG Data Consultant (from external firms) (8-10 years in consulting) and Senior Data Analyst/Scientist (with ESG specialisation) (8-12 years in data roles). Times vary with prior experience.

Where can a Lead ESG Performance Manager progress to?

This role can lead on to ESG Reporting & Performance Manager (3-5 years) and Principal ESG Data Architect (Individual Contributor) (3-5 years), depending on the skills you build.

What new skills matter most for a Lead ESG Performance Manager?

Increasingly, Prompt Engineering & LLM Integration for ESG and Data Storytelling & Visualisation for Impact. These are the skills our record of this role lists as growing.

Free tools

Want a read on where you stand?

Three free tools, no account needed. Each one ends with a role, a level and a way in.

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17Where to go from here

Other roles at Level 5

Same depth of qualification, different job. Useful if the work appeals but this particular role does not.

 More jobs in sustainability

Stay in the field you know and move sideways rather than up.
If you leave this industry

The skills built in this role, including data governance, assurance, regulatory interpretation and stakeholder influence, transfer well beyond one organisation. They can lead to ESG consulting, work with an ESG rating agency, a sustainable finance team at a financial institution, or data governance and risk management roles in other industries.

This role profile is © 2026 Growth Engineering Technologies Ltd. Built from UK occupational standards and regulated qualification data, and written for Zavmo.

You're not behind. You're right on time. The shift is only just beginning. Your role won't look the same in two years. Be the one who leads the change, not the one it happens to. Start my free Automation Fluency module What happens next: a free account, then we build your plan as you set up. No card. Build your plan, see your roadmap and meet the twelve tutors matched to you. All free. When you're ready to start learning, it's £70 a month, billed monthly. Cancel any time and billing stops.