Designing, building, optimising, and troubleshooting scalable batch and streaming data pipelines where applicable.
Contributing production-grade Python and SQL code aligned to engineering standards for maintainability, readability, observability, and operational resilience.
Supporting safe and pragmatic modernisation across legacy Pentaho and modern Databricks platform capabilities.
Improving Spark workload efficiency, query performance, orchestration reliability, storage optimisation, and platform scalability.
Contributing to technical investigations, troubleshooting, and remediation planning for production issues and systemic engineering weaknesses.
Implementing robust testing approaches including unit, integration, reconciliation, and data quality validation.
Improving supportability and resilience across the data estate through monitoring, dashboards, alerting, runbooks, and operational tooling.
Helping improve developer effectiveness through reusable tooling, templates, frameworks, and automation.
Supporting data-heavy and AI-enabled product initiatives including recommendation systems, behavioural analytics, propensity modelling, and intelligent automation features.
Collaborating with Data Engineers, Platform Engineering, SRE, Architecture, Governance, and Product teams to unblock delivery and support complex engineering challenges.

Strong hands-on experience designing, building, and operating scalable data pipelines and data platform workloads.
Experience with Pentaho ETL or similar ETL technologies in production environments.
Hands-on experience with Databricks, Spark, Delta Lake, or modern data platform technologies.
Strong Python and SQL engineering capability supported by solid software engineering fundamentals including testing, CI/CD, observability, packaging, and code quality.
Good understanding of distributed data processing, reliability, scalability, and failure handling.
Experience diagnosing and resolving production issues including performance bottlenecks, instability, and data quality problems.
Experience implementing modern data engineering patterns including CDC, idempotency, reconciliation, streaming concepts, backfills, and workload optimisation.
Experience operating production-grade data services with strong observability and operational support practices.
Strong collaboration and communication skills with the ability to work effectively across squads and technical disciplines.
A pragmatic engineering mindset with the ability to balance quality, reliability, delivery pace, and operational considerations.

A friendly, flexible and trust-based approach to working
25 days annual leave, plus usually a generous Christmas break
Premium private healthcare and dental care with Uniqa, available from day one
Flexi-Funds – a monthly allowance of 65 EUR to support bills and essential expenses in a way that works for you
Food vouchers – 60 EUR per month
Innovation and learning – space to develop skills, try new ideas and experiment, with an annual hackathon where some ideas make it into real work
A great office setup – free snacks and drinks every day
Access to the Storytel app for audiobooks and e-books
Bede Bucks – exclusive colleague discounts and access to a wellbeing platform
Lots of social events – both in and outside of working hours
Referral programme – help us grow the team and receive a referral bonus of up to 3,000 EUR (pre-tax, subject to scheme terms)
Bede swag – including hoodies, t-shirts and our much-loved Bede socks
Bede Holidays – extra discretionary days off through the year as a thank-you for the great work our teams do

Senior Data Engineer

Key skills