Lead Data Products Engineer
Skills
AdoptionApplication EngineeringCuratingData Protection ActEvolutionMeshModeling
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Senior or lead engineering experience in high-performing teams focused on data products
- Strong Python experience for data engineering and application engineering
- Deep knowledge of data management technologies including SQL NoSQL and Databricks
- Experience with cloud technologies and CI/CD pipelines
- Experience with Data Lakehouse architectures
- Practical knowledge of data mesh or data product architectures
- Experience designing data governance strategies with data quality and metadata focus
- Ability to communicate complex ideas clearly to technical and non-technical audiences
- Experience working with agile methods such as Scrum or Kanban
Nice to have
- Collaborative
- Curious
- Commercially aware
- Strategic mindset
- Domain driven
- Detail oriented
Day to day
- Lead the Data Products team and shape data products that support modelling processes and client-facing outputs
- Work closely with subject matter experts and the Platform team to design capture and transformation processes for the new Data and Processing Platform
- Own domain data products end to end including quality adoption reliability governance and evolution
- Formalise data contracts and guide engineering best practices with strong observability and reliability from the start
- Take an active role in agile delivery and continuously improve team processes and product design
Hiring process
- All applications are reviewed by Talent Acquisition
- No automated screening or AI-only hiring decisions
- Applications considered without discrimination
- Reasonable adjustments available on request