Role Overview
- You’ll lead complex engineering work across critical data pipelines and platform capabilities, acting as the technical quality bar for data engineering across the Tribe.
- This will include:
- Leading and implementing complex engineering work across critical data pipelines and platform capabilities.
- Taking the lead on difficult production incidents, performance bottlenecks, and data integrity issues.
- Driving root-cause analysis and remediation for systemic engineering and operational weaknesses.
- Designing, building, optimising, and troubleshooting scalable data pipelines across batch and streaming workloads where applicable.
- Contributing production-grade Python and SQL code aligned to engineering standards for maintainability, readability, observability, and operational resilience.
- Leading optimisation and stabilisation efforts across Pentaho ETL and Databricks lakehouse ecosystems.
- Improving Spark workload efficiency, cluster utilisation, query performance, storage optimisation, orchestration reliability, and platform scalability.
- Defining and implementing observability standards for critical pipelines and datasets.
- Improving operational readiness across the data estate through monitoring, alerting, dashboards, runbooks, ownership clarity, and operational tooling.
- Improving developer experience through reusable frameworks, CI/CD patterns, templates, libraries, and “golden path” implementation examples.
- Promoting pragmatic and safe adoption of AI-assisted and agentic engineering approaches where they improve engineering outcomes.
- Supporting data-heavy and AI-enabled product initiatives including recommendation engines, behavioural scoring, propensity modelling, and intelligent automation features.
- Designing and building production services, APIs, and integration layers that expose new data capabilities and features into products and operational workflows.
- Developing squad engineering leads through mentorship, coaching, technical guidance, and hands-on support.
- Collaborating with Data Engineers, Platform Engineering, SRE, Architecture, Governance, Product teams and engineering leadership to unblock delivery and support complex engineering challenges.
Requirements
- Strong hands-on experience designing, building, operating, and optimising enterprise-scale data platforms and pipelines.
- Experience with Pentaho ETL or similar technologies in large-scale production environments.
- Strong hands-on experience with Databricks, Spark, Delta Lake, and modern lakehouse engineering patterns.
- Advanced Python and SQL skills, supported by solid software engineering fundamentals including testing, CI/CD, observability, packaging, and code quality.
- Experience designing and building production services, APIs, and integration layers that bring data capabilities into products and business workflows.
- A strong understanding of distributed data processing, scalability, resilience, and failure handling.
- Experience diagnosing and resolving complex production issues, including performance, instability, and data integrity problems.
- Good knowledge of modern data engineering patterns including CDC, idempotency, streaming concepts, backfills, partitioning, and workload optimisation.
- Experience operating production-grade data services with strong observability and operational excellence practices.
- The ability to influence engineering direction and raise capability across multiple squads through technical credibility and collaboration.
- Experience mentoring senior engineers or technical leads in a complex engineering environment.
- Strong communication skills, with the ability to explain complex technical topics clearly to a range of audiences.
It would also be great if you have:
- Experience operating hybrid legacy and modern data platform estates.
- Experience with cloud-based data ecosystems, Azure preferred.
- Experience supporting data and AI product development initiatives.
- Exposure to recommendation systems, behavioural analytics, propensity modelling, or intelligent automation platforms.
- Practical experience applying AI-assisted or agentic tooling within engineering workflows.
- Experience operating within highly regulated, high-availability, or operationally sensitive environments.
Tech Stack
- Azure
- Cloud
- ETL
- Python
- Spark
- SQL
Benefits
- 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