Or Principal Data Engineer

Why join us

We’re a 150+ year-old business that operates on an incredible scale. There’s data from our 10 million+ Nectar users, days like Black Friday that make Argos the 3rd biggest website in the UK, and supply chain integration that gets the right products to the right locations on time, every time.

The technology we use is modern, scalable and constantly evolving, whether we’re in the cloud deploying over 1,000 microservices into AWS, Azure and GCP, or streaming billions of messages on Kafka and building event-based solutions. This is where you can broaden your technical knowledge and help solve complex problems while using your Agile skills to develop our long-lived teams.

As a Staff Engineer, you’ll help us bring together those complex horizontal outcomes that go beyond a single team and area, working with engineers and 3rd parties to deliver high quality and well-designed solutions.

What you’ll be doing

• Work with the Head of Engineering and Engineering Managers to shape technical priorities and reduce ambiguity, acting as a technical backbone to ensure balanced decisions across architecture, delivery, service and cost.
• Lead design reviews for complex data solutions, ensuring decisions are secure, scalable, cost-conscious, observable and aligned to platform standards.
• Create and evolve reusable engineering patterns for ingestion, transformation, orchestration, data quality, reconciliation, testing, monitoring, alerting and access control.
• Coach engineers and senior engineers through pairing, design critique, code review, incident learning, technical storytelling and pragmatic problem solving.
• Act as a bridge between engineering, product, architecture, data governance, security, BI Hub, Data & Analytics, and strategic partners so that outcomes are technically coherent and commercially sensible.
• Support the Definition of Ready process by helping teams clarify technical feasibility, dependencies, risks, data requirements, non‑functional requirements and route‑to‑build evidence before quarterly planning commitments are made.
• Stay close to delivery where your expertise makes the biggest difference: critical migrations, platform adoption, data quality improvements, incident prevention, supplier/service issues or strategically important customer data capabilities.

Key Responsibilities:

• Design and implement end-to-end data solutions that align with business objectives while adhering to best practices in data management and database performance.
• Define and communicate technical direction across multiple squads. Challenge local decisions where they create unnecessary complexity, risk, duplicated capability or long‑term support burden.
• Raise the quality bar for data products through clear ownership, robust testing, reconciliation, observability, lineage, documentation, performance and supportability.
• Collaborate with cross‑functional teams to address security, GDPR, PII handling, role‑based access, auditability and data governance are designed in from the start, not added later.
• Champion Sainsbury’s engineering standards, aligned autonomy and community practice; turn standards into practical patterns teams can adopt, improving resilience through monitoring, alerting, support runbooks, incident learning, data quality checks, cost controls and proactive simplification.

More about you:

• Strong practical experience designing and operating modern data platforms, pipelines and services across batch, streaming and event‑driven patterns.
• Deep understanding of engineering practice: clean design, testing strategy, CI/CD, infrastructure as code, observability, performance, security, incident response and Dev Sec Ops .
• Experience with cloud data services and modern data stacks. Relevant technologies may include Snowflake, Azure/AWS/GCP data services, Kafka, orchestration tooling, SQL, Python, dbt or equivalent transformation frameworks.
• Strong knowledge of data modelling, data quality, metadata/catalogue, reconciliation, lineage, role‑based access, privacy, GDPR/PII handling and data governance controls.
• Ability to reason about trade‑offs across cost, performance, resilience, supportability, delivery risk and strategic fit.
• Aware…