Quick overview
Job description
Sector: Tech
Reference: 16038
Principal Data Engineer
Manchester | Hybrid | Up to £85k DOE
Help shape the next chapter of our data capability. We’re looking for a hands-on Principle Data Engineer to own our data platforms: dependable, well-modelled and easy to build on. This is an opportunity to own the data platforms that power analytics across the business and give a small team the tools to do its best work.
What You'll Be Responsible For
As the Principal Data Engineer, you’ll own all data platforms while staying hands-on in the code. You’ll work alongside Engineering and AI/Data Science, lead and develop the data team and turn business needs into a realistic plan.
- Own the data platforms: Build and run ingestion, orchestration, the BigQuery warehouse, DBT tooling and Python data services on GCP, including CI/CD, infrastructure as code, access and cloud costs.
- Keep data reliable: Set freshness and recovery targets for critical data, own alerting and incident response, and make backfills and reruns safe.
- Model data for the business: Design layered warehouse models, from staging to dimensional marts.
- Partner across teams: Work alongside Engineering and AI/Data Science to provide the data they need, and fix data issues at source.
- Plan the work: Turn business and analytics requests into one prioritised backlog and roadmap.
- Set the engineering standard: Review SQL, Python and dbt code, keep tests and contracts strong and make every production change testable and reversible.
- Lead and develop the team: Line-manage and mentor members of the data team, through regular 1:1s, coaching, code review and career development.
Skills and Experience
Essentials
- Strong SQL and Python, building tested, maintainable production pipelines and data services.
- Hands-on experience with a cloud data warehouse, dbt (or equivalent) and workflow orchestration, including incremental loading, safe reruns and performance tuning.
- Data modelling for analytics and BI: dimensional design, semantic layers and well-documented shared datasets.
- Ownership of a production data platform on a major cloud: deployment, infrastructure as code, permissions, monitoring, incident recovery and cost.
- Sound security and data privacy practice, including GDPR and least-privilege access.
- Turning stakeholder needs into a prioritised backlog, and reconciling figures where finance reporting depends on them.
- Line management or mentoring of engineers, and technical leadership through code review and clear documentation.
- Experience with modern cloud data platforms, orchestration tooling, infrastructure as code and analytics platforms.
Desirables
- GCP experience with BigQuery, Composer and Cloud Run or Cloud Functions, including cost optimisation.
- Airbyte or similar ingestion tools, CDC, Kubernetes and data observability tools such as Elementary.
- Experience working with data scientists to put ML models or pipelines into production.
What You Will Get
- Competitive salary
- Competitive annual leave allowance
- Private medical insurance
- Flexible working arrangements
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