Data Engineer
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Summary
Data engineer building end-to-end operational resilience data solutions for a large UK organisation — data sourcing, ingestion, warehouse/refinery patterns and graph-based analysis (what-if, critical path/single points of failure). Core stack: SQL, Python, and Google Cloud Platform including BigQuery.
- Strong understanding of Operational Resilience concepts and hands‑on experience with relevant data e.g. service / impact tolerances, asset dependency incidents / outages, DR / BCP test evidence, concentration indicators
- Conceptual understanding of Procurement / Real Estate and associated data domains preferred
- Demonstrable understanding of graph concepts (nodes / edges, typed relationships, multi‑hop traversal / path analysis) and ability to apply in the context of Operational Resilience e.g. what-if analysis, identifying critical path / single point of failure
- Demonstrable experience in a data engineering role delivering end‑to‑end data solutions (data sourcing, ingestion, data warehouse / refinery patterns, data asset delivery)
- Strong SQL skills and experience with relational data modelling and optimisation
- Hands‑on experience with cloud data tooling and services (e.g. Google Cloud Platform, including BigQuery or equivalent)
- Strong coding capability in Python with solid software engineering practices (version control, testing, CI/CD where applicable)
- Experience with enterprise data technologies and platforms commonly used in large organisations and data integration patterns Template version: March 2020 ( when complete)
- Experience with data governance and operating discipline, metadata, lineage, access controls, retention, and data standards
- Experience with Agile delivery and familiarity with relevant tools (JIRA and Confluence).
- Strong written and verbal communication skills, including ability to work effectively with technical and nontechnical stakeholders