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Replaced a quarterly manual ESG data collection process with an automated pipeline ingesting energy, fleet, and supplier data. Reduced reporting preparation time by 84% and produced the company's first assurance-ready GRI and CSRD-aligned disclosure.
Replaced a quarterly manual ESG data collection process with an automated pipeline ingesting energy, fleet, and supplier data. Reduced reporting preparation time by 84% and produced the company's first assurance-ready GRI and CSRD-aligned disclosure.
Sustainability / ESG
Data Pipeline Engineering and ESG Reporting Automation
A mid-market logistics and facilities management group with 1,200 employees and operations across three EU countries faced rapidly escalating ESG reporting obligations under CSRD. Their existing process was entirely manual and unsustainable at the required frequency and quality:
The group required a reporting infrastructure that would:
The core challenge was not technical — it was data quality and process design. The existing data was scattered across 12 sites in incompatible formats:
Data Collection Reality at Project Start:
Calculation Complexity:
Assurance Requirement:
The client's investors had indicated a preference for limited assurance (rather than management assertion) on the FY2025 disclosure. This required audit-grade evidence — not just correct numbers, but a traceable, reproducible trail from source to disclosure.
We designed and built a four-layer ESG data pipeline over 14 weeks:
Layer 1: Ingestion (Weeks 1-4)
Layer 2: Transformation (Weeks 3-8)
Layer 3: Reporting Period Management (Weeks 7-10)
Layer 4: Outputs (Weeks 9-14)
Connected to four smart meter management platforms via REST APIs, pulling daily meter reads and aggregating to monthly totals per site and metering point. For utility PDF bills, deployed AWS Textract with a custom post-processing layer that validates extracted kWh values against expected ranges before accepting them into the clean layer. Error rate on PDF extraction dropped from manual error rate of 3.2% to 0.4% after two months of model tuning.
Wrote adapter layers for three telematics provider APIs (different schemas, authentication methods, and data update frequencies). Normalised all journey records to a canonical schema: vehicle ID, fuel type, distance (km), fuel consumed (litres or kWh for EVs), date. This normalisation layer made it possible to run a single Scope 1 fleet calculation model regardless of which telematics provider reported the data.
Built a lightweight supplier intake portal where supply chain partners submit activity data by Scope 3 category. Submissions are validated against plausibility rules (e.g. spend-to-weight ratios for Category 1) before ingestion. Non-conforming submissions trigger an automated request for clarification. Supplier coverage reached 68% of spend-weighted Category 1 emissions within one quarter of launch.
All 47 emission calculation models implemented as dbt transformations, with each model referencing the emission factor seed table by explicit version key. Running the same source data with different factor year versions produces labelled, distinguishable outputs — making restating for factor updates a controlled, documented process rather than a manual recalculation.
Designed a period-close workflow: at the end of each quarter, a designated sustainability manager runs the close process, which snapshots all calculation outputs into an immutable Parquet dataset in S3 with Object Lock. The snapshot carries a manifest of all source file hashes, dbt model versions, and emission factor versions used. This manifest is the primary exhibit for assurance reviewers.
Engaged with the client's chosen assurance provider (a Big 4 firm) six weeks before the first assurance review. Provided the assurance team with access to the audit evidence export tool, which produced a traceable record for any sampled metric on demand. The review completed in 3 weeks with 4 minor findings, all resolved within one week. The client received a clean limited assurance opinion on their FY2025 GRI 305 and ESRS E1 disclosures.
ESG reporting is becoming indistinguishable from financial reporting in its rigour and accountability requirements. This engagement demonstrated that the infrastructure gap between a credible disclosure and a spreadsheet-based estimate can be closed in a single project — and that the operational benefits (real-time site data, supplier transparency, faster reporting cycles) deliver business value beyond just regulatory compliance.
Next phase includes Scope 3 Category 11 (use of sold products) calculation models for the client's facilities management division, integration with building management systems for real-time energy intensity tracking, and a customer sustainability report portal for B2B clients requiring supply chain emission disclosures.
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