Principal Data Engineer
Summary
Hands-on principal-level data engineer who owns and shapes Google Cloud data platforms — BigQuery warehouse, dbt models, Python data services, CI/CD and IaC — while leading a small data team, setting engineering standards, and partnering with Engineering and Data Science to deliver reliable, well-modeled analytics data.
In this Principal Data Engineer role, you own and shape our data platforms on Google Cloud, ensuring reliable, well-modeled data foundations for analytics. You lead a small data team and work closely with Engineering and Data Science to translate business needs into practical plans. You drive platform ingestion, modeling, and governance while enabling cross-functional teams to leverage data effectively. This is a hands-on leadership role focused on scalable, secure data solutions that empower analytics at scale.
Pay / Benefits- competitive salary
- competitive annual leave allowance
- private medical insurance
- flexible working arrangements
- Own and operate data platforms, including ingestion, orchestration, BigQuery warehouse, dbt tooling, and Python data services on GCP; manage CI/CD, IaC, access, and cost control
- Ensure data freshness, reliability, alerting, incident response, and safe backfills/reruns
- Design layered data models for analytics, from staging to dimensional marts
- Collaborate with Engineering and AI/Data Science to meet data needs and address data issues at source
- Plan work by turning requests into a prioritized backlog and roadmap
- Set engineering standards: review SQL/Python/dbt code, enforce tests/contracts, and ensure reversible production changes
- Lead and develop the data team through mentoring, regular 1:1s, code reviews, and career development
- Strong SQL and Python for production data pipelines
- Hands-on experience with a cloud data warehouse, dbt or equivalent, and workflow orchestration (incremental loading, safe reruns, performance tuning)
- Data modelling for analytics (dimensional design, semantic layers, well-documented datasets)
- Experience owning a production data platform on a major cloud with IaC, permissions, monitoring, incident recovery, and cost management
- Security and data privacy practices including GDPR and least-privilege access
- Ability to translate stakeholder needs into a prioritized backlog and reconcile data for reporting
- Line management or mentoring of engineers and technical leadership via code reviews and documentation
- Experience with modern cloud data platforms, orchestration tooling, IaC, and analytics platforms
- Stakeholder management
- Prioritisation and backlog management
- Collaborative cross-functional working
- SQL
- Python
- Google Cloud Platform (GCP)