Data Engineer in Sheffield

The Role

Data Engineer within GCOO Data & Analytics to support the Operational Resilience programme by strengthening data foundations and accelerating delivery of trusted, well-governed data products across

Procurement and Real Estate Services.

The role will contribute to internal strategy to leverage the CxO Strategic Data Platform and publish reusable data products to the Data Fabric. These will be used to support the delivery of Business Service Owner MI, identification of operational asset vulnerabilities, and the modelling of resilience scenarios.

Your responsibilities:

• Lead technical delivery of data foundations for Operational Resilience, providing a governed, reusable data layer that underpins how the bank measures resilience, maps service dependencies and tests scenario assumptions across Procurement and Real Estate Services

• Design, build and operate robust data pipelines across the data lifecycle i.e sourcing, ingestion, transformation, modelling and publishing data assets

• Build, deploy and maintain Data Products aligned to common patterns & standards, including clear data contracts, quality rules, documentation, and operational runbooks

• Partner with Data Architects and Technology teams to implement solutions that meet architecture standards, technology controls, and non-functional requirements (performance, recoverability, auditability)

• Implement data quality, lineage and governance requirements, support metadata capture and stewardship activities (e.g. using tooling such as Collibra)

• Build data models (conceptual / logical / physical as appropriate) to enable consistent KPIs, dashboards and regulatory / management reporting outcomes

• Contribute to platform adoption by shaping and delivering datasets and data products optimised for the CxO Strategic Data Platform and Data Fabric publishing patterns

• Own technical delivery for relevant Data Products, manage backlog, define acceptance criteria, prioritise enhancements, and coordinate delivery with engineers / analysts and business stakeholders

• Identify and manage delivery risks, operational risks, and process blockers, ensure clear status reporting and dependency management across the programme

• Produce clear documentation (roadmaps, data dictionaries, architecture diagrams, operating procedures) in Confluence and maintain delivery traceability in JIRA

Essential skills/knowledge/experience:

Skills/experience required:

• • 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) PUBLIC Page 2 of 2

• • 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

Soft skills required:

• • Structured thinking and problem-solving, able to break complex problems into deliverable increments and make

• clear trade-offs

• • Ability to work independently, taking clear ownership of outcomes and managing timely delivery

• • Collaborative ways of working in cross-functional, geographically dispersed teams

• • Effective stakeholder management across business, technology, operations and risk partners

• • Pro-active, continuous-improvement mindset, spots opportunities to simplify, standardise, and scaleContinuous improvement: Proactively identifies inefficiencies and implements improvements to governance and delivery processes.

• Strives in ambiguity: Comfortable operating where requirements are evolving; able to create structure, propose options, and drive clarity.

• Problem Solver: Able to manage multiple moving parts and resolve blockers through collaboration and escalation when required.