Design, build, and maintain end-to-end data pipelines, including ingestion, transformation, and delivery of data to analytics and reporting layers.
Own and improve existing data pipelines, ensuring high reliability, performance, and scalability.
Set up new pipelines for internal and external data sources, selecting appropriate tools and patterns.
Monitor data quality, accuracy, and pipeline health, proactively identifying and resolving issues to ensure high data trust and uptime.
Implement best practices for BI engineering, including testing, documentation, version control, and observability.
Continuously improve data architecture and workflows to support growing data volumes and evolving business needs.
Partner with commercial, product, and operational stakeholders to understand their data needs, translating business questions into well-scoped BI engineering work.
Help shape and prioritise the BI engineering backlog, balancing technical improvements with high-impact business requests.

5+ years’ experience in a BI / Data engineering role.
Strong Python skills, with experience building ELT/ETL pipelines.
Strong SQL skills, with experience building and optimizing complex transformations.
Experience developing data pipelines using modern data stack tools (e.g. ELT/ETL frameworks, cloud data warehouses, orchestration tools).
A Degree in Computer Science, Engineering, Mathematics, Statistics, Economics or another quantitative field (or equivalent work experience).
Solid understanding of data modelling concepts and analytics-ready schemas.
Demonstrated experience managing relationships with business stakeholders, including scoping data requirements, setting expectations, and delivering against commercial priorities.

Lead BI Engineer

Key skills