Environmental Data Analyst

Role Purpose & Context

Role Summary

The Environmental Data Analyst is responsible for the accurate collection and initial processing of environmental data, which directly impacts our regulatory compliance and public reputation. You'll work closely with our site teams and the wider reporting function, translating raw operational figures into structured data that our Environmental Reporting Specialists use for analysis and submission. When this role is done well, our reports are robust, credible, and free from errors, helping us avoid fines and maintain investor trust. When it's not, we risk regulatory penalties, reputational damage, and losing credibility with our stakeholders. The challenge here is the sheer volume and inconsistency of data you'll encounter, often from disparate sources. The reward is knowing your meticulous work underpins our entire environmental transparency effort, making a real difference to how we're perceived.

Reporting Structure

• Reports to: Environmental Reporting Specialist
• Direct reports:
• Matrix relationships: Junior ESG Reporting Assistant, Sustainability Data Coordinator, Compliance Data Entry Specialist,

Key Stakeholders

Internal:

• Site Operations Managers (for data collection)
• Finance Department (for utility bills, procurement data)
• Environmental Reporting Specialists (your direct team)
• IT Support (for system access issues)
• Health & Safety teams (for incident data)

External:

• External Auditors (indirectly, through data preparation)
• EHS Software Vendors (for basic platform queries)

Organisational Impact

Scope: Your work directly supports the Environmental Reporting team in meeting strict deadlines for environmental disclosures, like CDP and GRI. If the data isn't accurate or on time, the whole reporting process grinds to a halt, which can lead to missed deadlines, regulatory non-compliance, and ultimately, damage our company's standing with investors and the public. You're the first line of defence against bad data getting into our reports, so your attention to detail really matters.

Performance Metrics

Quantitative Metrics

1. Metric: Data Accuracy
2. Desc: The percentage of data points entered or processed without error.
3. Target: >99% accuracy on all data entry tasks
4. Freq: Monthly, via spot checks and validation reports
5. Example: Out of 1,000 data points entered for Q1 energy consumption, you've got fewer than 10 errors. That's what we're aiming for.
6. Metric: Timeliness of Data Submission
7. Desc: Meeting internal deadlines for collecting and submitting raw data from various sites.
8. Target: 100% of data collection templates submitted by internal deadlines
9. Freq: Weekly/Monthly, tracked against reporting calendar
10. Example: If the deadline for site X's waste data is Friday, it's in by Friday, every time. No chasing needed.
11. Metric: Query Resolution Rate
12. Desc: How quickly and effectively you resolve basic data validation queries from your manager or site contacts.
13. Target: Resolves 95% of data validation queries within 48 hours
14. Freq: Weekly, tracked by query log
15. Example: Your manager spots an odd number in the water usage. You investigate, find the reason (e.g., a new cooling tower), and explain it clearly within two days.
16. Metric: Data Completeness
17. Desc: Ensuring all required data fields are populated for each reporting period.
18. Target: >98% completeness for all assigned data sets
19. Freq: Quarterly, during data consolidation
20. Example: You've made sure that for every site, we have electricity, gas, and water consumption figures, not just two out of three.

Qualitative Metrics

1. Metric: Adherence to Procedures
2. Desc: Consistently following established data collection, entry, and validation procedures.
3. Evidence: Your work consistently aligns with our internal process documentation. You'll be able to show the audit trail for any data point, and your manager won't find you cutting corners. Your data sets are always organised the way we expect them to be.
4. Metric: Proactive Problem Spotting
5. Desc: Identifying potential data issues or inconsistencies before they become bigger problems.
6. Evidence: You flag an unusual spike in energy use at a particular site, even if it's within 'acceptable' limits, because it just 'feels' wrong. You'll bring these things to your manager's attention, asking 'Does this look right to you?'
7. Metric: Communication Clarity
8. Desc: Clearly communicating data requests and status updates to internal stakeholders.
9. Evidence: Site managers understand exactly what data you need and by when. Your emails are concise, polite, and leave no room for misunderstanding. You'll ask for clarification when you don't understand something, rather than guessing.
10. Metric: Learning & Development
11. Desc: Actively seeking to understand environmental reporting principles and improving technical skills.
12. Evidence: You'll ask thoughtful questions about 'why' we report certain things. You'll show initiative in learning new Excel functions or basic EHS platform features. You're keen to understand the bigger picture of what we do.

Primary Traits

• Trait: Forensic Detail-Orientation
• Manifestation: You're the person who notices the plant reported energy in MWh while all others used GJ, and you know that's a problem. You'll meticulously check data sets before they're even looked at by others, spotting that one rogue zero or a misplaced decimal point. You're the one who keeps a meticulous audit trail for every single data point, knowing exactly where it came from.
• Benefit: Honestly, a single incorrect decimal point in an emissions report isn't just a typo; it can lead to regulatory fines, a drop in our ESG ratings, and public reputational damage. This role is our first line of defence against those costly errors. We need someone who double-checks instinctively, not because they've been told to, but because it feels wrong not to.
• Trait: Diplomatic Tenacity
• Manifestation: You'll be following up with a busy Plant Manager for the fifth time to get their waste disposal data, each time with a polite, professional, and clear request. You're good at building those informal relationships with data providers, so they understand *why* their data is important to you, even if they have other priorities. You don't give up easily, but you're never rude about it.
• Benefit: The truth is, the data we need for reporting is scattered across dozens of departments and global sites. Success here depends entirely on your ability to influence colleagues who have their own deadlines, without having any direct authority over them. You've got to be persistent, but always with a smile.
• Trait: Structured Scepticism
• Manifestation: You'll receive a data point and your first thought isn't 'great, another number' but 'How was this measured? What's the source? Does this number make sense compared to last year's?' You're not afraid to gently push back on data that 'looks odd' until a logical explanation is found. You're always asking 'why' and 'how' something was calculated.
• Benefit: It's simple: garbage in, garbage out. This role isn't just about collecting data; it's about validating it. Taking data at face value risks embedding errors into our public disclosures and, frankly, into strategic decisions. We need someone who questions, politely but firmly, to ensure our data is sound.

Supporting Traits

• Trait: Methodical & Process-Driven
• Desc: You'll honestly thrive on creating and following checklists and standardised procedures. You like things organised and predictable, especially when it comes to data.
• Trait: Clear Communicator
• Desc: You can explain a data request or a simple environmental concept to someone who isn't an expert, making it easy for them to understand what you need. No jargon, just plain English.
• Trait: Unquestionable Integrity
• Desc: You deeply understand the ethical gravity of the data you handle. You'd never, ever feel comfortable manipulating figures, even if there was subtle pressure to do so. Honesty is paramount.

Primary Motivators

1. Motivator: Making a Tangible Impact Through Accuracy
2. Daily: You'll get genuine satisfaction from knowing that the clean, accurate data you've prepared is directly contributing to our company's credible environmental reports. You'll see the numbers you've painstakingly checked appear in public documents, knowing they're trustworthy.
3. Motivator: Learning and Developing Expertise
4. Daily: You're keen to understand the 'why' behind environmental reporting, not just the 'what'. You'll actively ask questions, absorb new information about regulations and frameworks, and enjoy building your knowledge base in a critical area.
5. Motivator: Contributing to a Greater Good
6. Daily: While the day-to-day might be about spreadsheets, you're motivated by the bigger picture – helping the company be more transparent and responsible about its environmental impact. You believe in the importance of good environmental data.

Potential Demotivators

Let's be real, this job isn't for everyone. If you need constant external validation or get bored by repetitive tasks, you might struggle. You'll spend a fair bit of time as the 'data janitor', chasing, cleaning, and formatting inconsistent data from dozens of Excel sheets, emails, and legacy systems. This can feel less like high-value analysis and more like administrative grunt work. You'll probably experience the 'urgent' executive request that derails your carefully planned schedule, only for it to be deprioritised a day later. If you need to see every piece of your work make it to a glamorous, finished product, you might find it frustrating that some of your meticulous data gathering just becomes a small part of a much larger report that few people read in its entirety.

Common Frustrations

1. The constant battle with siloed systems: energy data in one place, waste in another, travel with HR. You're often the human API.
2. Dealing with incomplete or inconsistent data from various sites, requiring endless follow-ups and clarifications.
3. The feeling that your meticulous work is sometimes overlooked, as it's a foundational, behind-the-scenes role.
4. Having to explain basic data requirements repeatedly to busy operational staff who have other priorities.

What Role Doesn't Offer

1. High-level strategic decision-making or setting the company's environmental strategy.
2. A lot of direct external stakeholder engagement or public speaking opportunities.
3. A role where every day is completely different; there's a strong cyclical, routine element to environmental reporting.
4. The chance to build complex data models or perform deep statistical analysis from day one.

ADHD Positives

1. The clear, structured processes for data entry and validation can provide a helpful framework, reducing ambiguity.
2. The need for meticulous detail and spotting anomalies can be a strength, as hyperfocus can be applied to data integrity.
3. The cyclical nature of reporting means predictable tasks, which can be comforting for some.

ADHD Challenges and Accommodations

1. Repetitive data entry tasks might become monotonous; we can look at breaking these into shorter, focused blocks with micro-breaks.
2. Dealing with multiple, often fragmented data sources could be overwhelming; we'll provide clear checklists and prioritise tasks to manage this.
3. Potential for 'urgent' requests to derail focus; we'll help you prioritise and protect your time for core tasks, escalating when necessary.

Dyslexia Positives

1. The strong emphasis on numerical data and pattern recognition can be a strength, as numbers are often less ambiguous than text.
2. Structured data templates and clear process documentation can reduce reliance on free-form writing and complex textual instructions.
3. Tools with strong visual cues and error highlighting can be very helpful for data validation.

Dyslexia Challenges and Accommodations

1. Reading and interpreting lengthy regulatory documents or complex written instructions might be challenging; we can provide summaries or use text-to-speech software.
2. Proofreading reports or emails for grammatical errors could be difficult; we encourage using grammar checkers and peer review for important communications.
3. We can offer tools like screen readers or coloured overlays if they help with reading dense spreadsheets or documents.

Autism Positives

1. The role's focus on logic, data, and adherence to precise procedures can be a good fit, as it often involves clear rules and predictable outcomes.
2. The need for deep analytical focus on data integrity and spotting inconsistencies aligns well with a detail-oriented approach.
3. The structured nature of reporting cycles provides a predictable routine, which can be reassuring.

Autism Challenges and Accommodations

1. Unexpected changes to reporting requirements or 'urgent' requests might cause distress; we'll provide as much advance notice as possible and clear communication channels for changes.
2. Interacting with multiple internal stakeholders for data collection might be socially demanding; we can support with clear communication templates and allow for email-first interactions where possible.
3. Sensory overload from a busy open-plan office could be an issue; we can discuss workstation adjustments, noise-cancelling headphones, or flexible work options.

Key Responsibilities

Experience Levels Responsibilities

1. Level: Entry Level (0-2 years)
2. Responsibilities: Collect raw environmental data (like energy bills, water meter readings, waste manifests) from various internal departments and site contacts, making sure you get everything needed by the deadline.
3. Accurately enter collected data into our EHS software platforms (like Enablon or Sphera) and maintain organised spreadsheets, following our established data entry protocols to the letter.
4. Perform initial validation checks on incoming data – that means spotting obvious errors, missing values, or numbers that just don't look right, and flagging them to your manager.
5. Assist the Environmental Reporting Specialists with preparing data for internal reviews and external audits, which usually involves pulling specific reports or compiling audit trails.
6. Maintain and update our internal documentation for data collection processes, making sure it's always clear and easy for others to follow. Yes, it's boring, but future-you will be grateful.
7. Support with basic administrative tasks related to environmental reporting, such as scheduling meetings, organising files, and responding to simple data requests.
8. Learn the ins and outs of key environmental reporting frameworks like GRI, SASB, and CDP, understanding what data points are needed for each and why they matter.
9. Supervision: You'll have daily check-ins with your Environmental Reporting Specialist or Senior Specialist. Most tasks will be assigned with clear instructions, and your work will be reviewed before it's finalised. Think of it as paired work initially, moving to more independent tasks as you get the hang of things.
10. Decision: Honestly, you won't be making independent decisions in this role. Any questions about data interpretation, process changes, or significant discrepancies should be escalated immediately to your manager. Your job is to gather and validate, not to decide. You'll inform your manager of any issues, but they'll make the call.
11. Success: You're doing well if your data is consistently accurate, you meet your internal deadlines, and you're proactively flagging any data oddities. We'll also be looking for you to ask thoughtful questions and show a genuine interest in learning the broader context of environmental reporting. Basically, if you're reliable, meticulous, and keen to learn, you're succeeding.

Decision-Making Authority

• Type: Data Interpretation (e.g., how to categorise a specific waste stream)
• Entry: Escalate to Environmental Reporting Specialist for guidance and final decision.
• Mid: Propose a solution to manager, get approval before proceeding.
• Senior: Make technical decision within established guidelines, inform manager.
• Type: Process Improvement (e.g., changing a data collection template)
• Entry: Suggest ideas to manager, but no authority to implement.
• Mid: Propose and pilot small improvements with manager's approval.
• Senior: Design and implement process improvements within a workstream.
• Type: External Communication (e.g., responding to a supplier data request)
• Entry: Draft response for manager's review and approval. No direct external contact without supervision.
• Mid: Respond to routine external queries within defined scope, escalate complex ones.
• Senior: Represent the team in routine external communications, consult on complex issues.
• Type: Software Configuration (e.g., setting up a new data field in Enablon)
• Entry: No authority. Report system issues or needs to manager.
• Mid: Configure minor elements with manager's approval and guidance.
• Senior: Design and implement significant configurations, manage user access.

Competency Requirements

Foundation Skills (Transferable)

Beyond the technical stuff, there are some fundamental skills you'll need to thrive here. These are the building blocks for any successful career, especially in a role that relies heavily on accurate data and clear communication. We're looking for someone who's ready to learn and apply these day-to-day.

• Category: Communication & Collaboration
• Skills: Active Listening: Really hearing what colleagues need when they describe data sources or issues.
• Clear Written Communication: Writing concise, unambiguous emails for data requests and updates.
• Verbal Clarity: Explaining simple data concepts or issues in plain English to non-experts.
• Teamwork: Working effectively with your direct manager and other specialists to achieve reporting goals.
• Category: Problem-Solving & Initiative
• Skills: Root Cause Analysis (Basic): Identifying why a data point looks off or why a report isn't running correctly.
• Structured Thinking: Approaching tasks in a logical, step-by-step manner.
• Resourcefulness: Knowing when to ask for help and where to find information (e.g., internal documentation, team members).
• Proactive Learning: Taking the initiative to understand new processes or tools without constant prompting.
• Category: Organisation & Adaptability
• Skills: Time Management: Juggling multiple data requests and deadlines effectively.
• Prioritisation: Knowing what needs to be done first, especially when things get busy.
• Attention to Detail: Spotting tiny errors in large datasets (this is huge for us).
• Adaptability (Basic): Being able to adjust when a data source changes or a deadline shifts slightly.
• Category: Integrity & Ethics
• Skills: Data Confidentiality: Understanding and respecting the sensitivity of the data you handle.
• Ethical Conduct: Always ensuring data is presented truthfully and accurately, resisting any pressure to 'spin' numbers.
• Transparency: Documenting your work clearly so others can follow your logic and data lineage.

Functional Skills (Role-Specific Technical)

This is where the rubber meets the road. You'll need a solid grasp of certain technical and domain-specific skills to hit the ground running, especially when it comes to handling environmental data and using our core systems. Don't worry, we'll teach you the specifics, but a good foundation is key.

Technical Competencies

• Skill: Sustainability Reporting Frameworks (Basic)
• Desc: A basic understanding of what frameworks like GRI Standards, SASB Standards, and CDP are, and why companies use them. You'll know which data points relate to which framework, but won't be interpreting complex requirements.
• Level: Basic
• Skill: Greenhouse Gas (GHG) Protocol (Basic)
• Desc: An awareness of Scope 1, 2, and 3 emissions, and what types of activities fall into each. You'll understand the concept of emission factors and why they're used, but won't be calculating complex inventories yourself.
• Level: Basic
• Skill: Data Assurance & Verification (Awareness)
• Desc: Understanding that our data needs to be 'assurance-ready' for external auditors. You'll know what an audit trail is and why meticulous documentation is crucial, even if you're not managing the audit process.
• Level: Basic
• Skill: Environmental Management Systems (Awareness)
• Desc: A general understanding of what an EMS (like ISO 14001) is designed to do – manage environmental impacts systematically. You'll see how the data you collect feeds into these systems.
• Level: Basic

Digital Tools

• Tool: Microsoft Excel (Power Query, Pivot Tables)
• Level: Intermediate
• Usage: You'll be using VLOOKUP/XLOOKUP to match data, Pivot Tables to quickly aggregate numbers, and basic formulas to clean and transform raw data from various sources. We're talking about more than just basic sums here.
• Tool: EHS & ESG Platforms (e.g., Enablon, Sphera)
• Level: Intermediate
• Usage: You'll be regularly entering data into these platforms, running pre-configured reports, and validating your inputs against the original source documents. You'll get comfortable navigating the system and understanding its structure.
• Tool: Data Visualization (e.g., Power BI, Tableau)
• Level: Basic
• Usage: You'll mostly be viewing and interacting with existing dashboards, filtering data, and exporting visuals for presentations. You won't be building them from scratch, but you'll need to understand how to pull information from them.
• Tool: Collaboration & PM (e.g., MS Teams, Confluence)
• Level: Intermediate
• Usage: You'll be using MS Teams for daily communication, contributing to documentation in Confluence (our knowledge base), and updating tasks in our project management tools to track your progress.
• Tool: SQL (basic queries)
• Level: Basic
• Usage: You should be able to run existing SQL queries to pull specific data sets from our databases. You won't be writing complex joins, but understanding how to execute a pre-written query is helpful.

Industry Knowledge

• Area: Environmental Regulations (Basic)
• Desc: A general awareness of key environmental regulations relevant to our industry, understanding that compliance is non-negotiable. You'll know *of* them, but not necessarily the intricate details.
• Area: Data Governance Principles
• Desc: Understanding the importance of data quality, consistency, and security in an environmental reporting context. You'll know why we have rules around how data is handled.

Regulatory Compliance Regulations

• Reg: EU Corporate Sustainability Reporting Directive (CSRD) / ESRS (Awareness)
• Usage: You'll understand that CSRD is coming and why it's driving much of our data collection. You'll know that 'double materiality' is a thing, but won't be conducting assessments yourself. Your role is to help gather the data that feeds into these requirements.
• Reg: UK Streamlined Energy and Carbon Reporting (SECR) (Awareness)
• Usage: You'll know that SECR requires us to report on energy use and carbon emissions in the UK. Your data collection will directly contribute to our SECR submission.
• Reg: Task Force on Climate-related Financial Disclosures (TCFD) (Awareness)
• Usage: You'll understand that TCFD is about disclosing climate risks and opportunities. The data you collect helps inform these disclosures, even if you're not writing the narrative.

Essential Prerequisites

• A proven track record of meticulous attention to detail, perhaps from a data entry, administrative, or scientific lab role.
• Solid intermediate skills in Microsoft Excel, including VLOOKUPs, Pivot Tables, and basic formula creation.
• A genuine interest in environmental sustainability and why accurate reporting matters.
• The ability to follow instructions precisely and work within established procedures.
• Strong organisational skills; you know how to keep files tidy and track multiple small tasks.

Career Pathway Context

We're looking for someone who's ready to roll up their sleeves and get stuck into the data. You don't need to be an environmental expert yet, but you do need to be eager to learn and have a natural knack for numbers and organisation. This role is a fantastic entry point if you're passionate about environmental data and want to build a career in sustainability reporting.

Qualifications & Credentials

Emerging Foundation Skills

• Skill: Basic AI Prompt Engineering
• Why: AI tools are already here, and they're getting better at helping with routine tasks. Learning how to talk to them effectively will make your job much easier and faster, allowing you to focus on validation and critical thinking.
• Concepts: [{'concept_name': 'Clear Instructions', 'description': 'How to write prompts that give AI specific, unambiguous tasks for data extraction or summarisation.'}, {'concept_name': 'Context Provision', 'description': 'Understanding what background information an AI needs to give you a useful output.'}, {'concept_name': 'Output Validation', 'description': 'Knowing that AI outputs need to be double-checked, not blindly trusted.'}, {'concept_name': 'Ethical Use', 'description': 'Understanding the importance of data privacy and not putting sensitive information into public AI tools.'}]
• Prepare: This week: Experiment with ChatGPT or Claude to summarise articles about environmental reporting.
• This month: Use an AI tool to help draft a simple data request email, then refine it yourself.
• Month 2: Explore how AI could help categorise basic data points from a spreadsheet.
• Month 3: Document one specific task where AI saved you time and share it with your manager.
• QuickWin: Start using AI to draft email responses or summarise internal meeting notes today. No formal training needed, just dive in and experiment.
• Skill: Understanding Data Lineage (Advanced)
• Why: With increasing scrutiny on ESG data, being able to trace every number back to its original source is becoming critical. This isn't just about 'knowing' the source, but being able to *prove* it, which is essential for auditability.
• Concepts: [{'concept_name': 'Source Documentation', 'description': "Understanding what constitutes a valid 'source' (e.g., utility bill, sensor reading, signed manifest)."}, {'concept_name': 'Version Control', 'description': 'Knowing how to track changes to data and documents over time.'}, {'concept_name': 'Audit Trails', 'description': 'Creating clear, step-by-step records of how data was collected, transformed, and entered.'}, {'concept_name': 'Data Integrity', 'description': 'Ensuring data remains accurate and unaltered throughout its lifecycle.'}]
• Prepare: This week: For every piece of data you enter, make a note of its exact source and date.
• This month: Ask your manager to walk you through an example of a good 'audit trail' for a specific data point.
• Month 2: Practice documenting your own data collection process in detail, as if an auditor were watching.
• Month 3: Help improve one piece of existing process documentation to make the data lineage clearer.
• QuickWin: Start a simple log for every spreadsheet you work on: who touched it, when, and what they changed. It's a small step, but it builds good habits.

Advancing Technical Skills

• Skill: Advanced Excel for Data Transformation
• Why: While EHS platforms are great, you'll still get a lot of messy data in Excel. Mastering Power Query and more complex formulas will allow you to clean and prepare data much faster and more reliably, reducing manual errors.
• Concepts: [{'concept_name': 'Power Query Editor', 'description': 'Using this tool to connect to various data sources, clean, transform, and reshape data without manual copy-pasting.'}, {'concept_name': 'Conditional Formatting for Validation', 'description': 'Setting up rules to automatically highlight potential errors or outliers in your spreadsheets.'}, {'concept_name': 'Array Formulas (Basic)', 'description': 'Using more advanced formulas to perform calculations on multiple items at once, making your spreadsheets more efficient.'}, {'concept_name': 'Data Validation Rules', 'description': 'Setting up rules in Excel to prevent incorrect data from being entered in the first place.'}]
• Prepare: This week: Watch a few YouTube tutorials on Excel Power Query basics.
• This month: Try to use Power Query to clean one of your recurring messy data sets.
• Month 2: Build a dynamic dashboard in Excel using Pivot Tables and Power Query.
• Month 3: Share a new Excel trick you've learned with your team.
• QuickWin: Start using Excel's 'Text to Columns' and 'Remove Duplicates' features more often. They're simple but powerful.
• Skill: EHS Platform Configuration (Basic)
• Why: As you get more comfortable with our EHS platforms, you'll start to see how they can be optimised. Understanding basic configuration will allow you to suggest improvements and even make small changes yourself, increasing your value to the team.
• Concepts: [{'concept_name': 'Data Field Types', 'description': 'Understanding the different types of fields (e.g., text, number, date, dropdown) and why they matter.'}, {'concept_name': 'User Permissions (Basic)', 'description': 'Knowing how different users have different access levels within the platform.'}, {'concept_name': 'Report Customisation (Basic)', 'description': 'Learning how to modify existing reports to pull slightly different data or views.'}, {'concept_name': 'Workflow Understanding', 'description': 'Mapping out how data flows through the system from input to final report.'}]
• Prepare: This week: Ask your manager to show you how a new data field is created in our EHS platform.
• This month: Spend time exploring the 'admin' or 'settings' sections (if you have view-only access) to understand the backend.
• Month 2: Suggest a small improvement to a data entry form or a report layout.
• Month 3: Document a common user issue and propose a simple configuration fix.
• QuickWin: Familiarise yourself with all the existing reports in our EHS system. What data do they show? How are they structured?

Education Requirements

• Level: Minimum
• Req: A-Levels or equivalent vocational qualifications (e.g., BTEC Level 3) in a numerate subject (Maths, Science, Business) or Environmental Studies.
• Alts: We're open to candidates who can demonstrate equivalent practical experience in a data-heavy administrative role, even if they don't have formal qualifications at this level. Show us you can handle numbers and pay attention to detail!
• Level: Preferred
• Req: A Bachelor's degree (or equivalent OFQUAL Level 6 qualification) in Environmental Science, Sustainability, Data Science, Business Analytics, or a related field.
• Alts: While a degree is great, we value practical skills and a keen mind. If you've got a strong portfolio of data handling projects or relevant work experience, we'd still love to hear from you.

Experience Requirements

You'll ideally have 0-2 years of experience in a role that involved significant data handling, data entry, or administrative support, especially if it was in an environmental, scientific, or compliance-focused setting. We're looking for someone who has experience meticulously collecting information, checking for errors, and organising it systematically. This could be anything from managing lab results to processing invoices or maintaining a large database. Experience with Excel is a must, and any exposure to EHS software would be a bonus.

Preferred Certifications

• Cert: IEMA Foundation Certificate in Environmental Management
• Prod: IEMA (Institute of Environmental Management & Assessment)
• Usage: Shows a foundational understanding of environmental management principles, which is directly relevant to the data you'll be handling.
• Cert: Microsoft Certified: Excel Associate
• Prod: Microsoft
• Usage: Demonstrates a strong, verified proficiency in Excel, which is a core tool for this role.

Recommended Activities

• Attending webinars or online courses on specific environmental reporting frameworks (e.g., a free GRI Standards introduction).
• Joining relevant professional networks or LinkedIn groups to stay updated on industry trends.
• Seeking out internal mentors within the Compliance_Quality_Health_Safety department to learn more about broader compliance topics.
• Practising advanced Excel functions and Power Query on personal or dummy datasets to build confidence.

Career Progression Pathways

Entry Paths to This Role

• Path: Administrative Assistant / Data Entry Clerk
• Time: 1-2 years
• Path: Science / Lab Technician
• Time: 0-2 years
• Path: Recent Graduate (Environmental/Data Science)
• Time: 0 years

Career Progression From This Role

• Pathway: Environmental Reporting Specialist
• Time: 2-3 years

Long Term Vision Potential Roles

• Title: Senior Environmental Reporting Specialist
• Time: 5-8 years
• Title: Lead Environmental Reporting Strategist
• Time: 8-12 years
• Title: International Environmental Reporting Manager
• Time: 12-16 years
• Title: Director of Sustainability & ESG Reporting
• Time: 16-20 years

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.