Principal Data Engineer
Summary
A 50/50 hands-on Principal Data Engineer role on an established enterprise data team: architect, build and optimise scalable, secure AWS data pipelines and data lake/lakehouse platforms using Python, Spark, dbt, Airflow and Redshift, while mentoring engineers, driving DataOps/governance and implementing SageMaker.
Are you ready to architect the future of data in a high-performance, mission-critical environment?
Come and join this established enterprise data team and lead and own the design and development of scalable, secure data solutions on AWS.
In this 50/50 hands on role you’ll architect and optimise data pipelines, mentor engineers, and collaborate with stakeholders to deliver high-performance, future-ready data products.
You’ll also have an opportunity to implementSageMaker!
Key responsibilities:
- Lead end-to-end data platform architecture
- Design scalable data lake and data mesh solutions
- Build reusable data engineering frameworks and tools
- Partner with stakeholders to deliver effective data solutions
- Drive DataOps, CI/CD, automation and observability
- Embed security, privacy, governance and reliability
What we’re looking for:
- Strong AWS data platform and pipeline experience.
- Expertise in Python, Spark, dbt and Airflow.
- Strong knowledge of distributed systems and data architecture.
- Experience with Redshift, Iceberg and data lakehouse patterns.
- Proven experience leading data platform design and governance.