- Set a costed, sequenced multi-year roadmap and investment portfolio across CMMS/EAM, PIM/PLM, integration, telemetry, and the data platform.
- Establish canonical asset identity, taxonomy, hierarchy, configuration, and BOM standards, with a system of record for each critical data object.
- Lead data cleansing and validation-at-source programmes to replace spreadsheets with governed lifecycle data.
- Deliver a unified asset and topology model with OT/IT ingest and IEC 62443-aligned segmentation.
- Publish data-quality scores and align shared definitions for PUE, WUE, capacity, stranded power, and availability.
- Own CMMS/EAM configuration baselines and controlled SOP/MOP/EOP libraries; map condition data to assets so predictive maintenance raises work orders.
- Build anomaly detection, remaining-useful-life prediction, and thermal and power optimisation, and progress control loops through defined safety and approval stages.
- Turn L1–L5 commissioning into data, set handover acceptance gates, and quantify readiness by hall and site.
- Benchmark readiness across the portfolio and act as senior escalation point across engineering, procurement, construction, operations, reliability, platform, finance, and HSE.
- Build and develop a team spanning lifecycle engineering, data science, and data engineering.
Machine Learning