Senior Governance, Risk & Compliance Manager · vacancy
Here's what AI can do for this role — and what still needs a human. Built straight from ENSEK's own job advert, running live on my_db.ensek_demo.energy_customers_360 — 27,640,145 real rows via MotherDuck (DuckDB). Not a slide about AI. The job, getting done.
Every line on the left is lifted from ENSEK's actual job ad. If a card lacks a harvested JD line, it is omitted. On the right is the AI doing it — with eligible cards running live against the warehouse and offline inspection clearly labelled in the workspace.
“Support the Head of GRC in developing, implementing and maintaining the organisation’s governance framework to support effective oversight, accountability and decision-making.”
What is the Consumer Duty vulnerability baseline — how many properties carry fuel-poverty risk, what do they pay, and how does their bill compare to the rest of the book?
kpi“Help develop and maintain the enterprise and operational risk registers, identifying emerging risks, and ensuring appropriate mitigations are in place.”
Which privately-rented properties are sub-MEES threshold (EPC F or G) and therefore non-compliant with the Minimum Energy Efficiency Standard?
deviation“Identify, assess, prioritise and monitor risks that may impact the organisation’s operations, assets, obligations or strategic objectives.”
How large is the ECO4-eligible cohort, and what is the saveable carbon and efficiency gap available to meet the obligation by EPC band?
bar chart“Work with stakeholders to design, implement and monitor effective controls to reduce risk exposure and strengthen organisational resilience.”
Which regions have the highest concentration of fuel-poverty-risk properties with above-average bills — the affordability risk heat-map for the CFO?
bar chart“Produce high-quality management information and dashboards that give leadership clear visibility of assurance performance, audit status, and risk exposure.”
What does the cross-obligation risk matrix look like — how does EPC band intersect with tenure to identify where MEES, ECO4 and Consumer Duty obligations concentrate?
tableThe honest other half. AI does the analysis; a person owns the decision — especially where regulation, fairness and accountability bite.
A plain-English question — the same one the job ad describes — is translated to SQL by the agentic backend.
Curated cards run server-side against MotherDuck when eligible. The workspace separately labels any local inspection path.
Runs against my_db.ensek_demo.energy_customers_360 (27,640,145 rows declared by the manifest). No synthetic numbers.
Each figure carries a falsifier — recomputed from the result set, not a stored number, so it can't quietly drift.
It's the role getting done: curated questions run live server-side against the warehouse; local inspection is labelled inside the workspace.
Open the live workspace →Provenance. Offline degrade: labelled 5,000-row slice of the REAL ensek_demo.energy_customers_360 view — 27,640,145 national properties enriched with property valuations, area affluence, tenure and flood risk. No PII (address, postcode, account_id excluded). Proportions representative; absolute counts are slice-scale. Live server-side path: my_db.ensek_demo.energy_customers_360 (27.6M rows). Dormant until operator provisions MOT
It's Sorted — I took ENSEK's job ads and didn't write a report on what AI could do. I built it. Get the rest sorted →
I'm trained on this proof and the real ENSEK: the Ignition meter-to-cash platform (seven modules), the move under Centrica in 2024, 7M+ energy accounts migrated for suppliers like British Gas and Utility Warehouse, and the Ofgem framing. Ask me how the Data Analyst function changes shape, or which open roles map to which Ignition module.