Build, maintain, and enhance data pipelines using SQL and Python to ingest, transform, and serve data from core product systems and third-party sources.
Develop and maintain well-modelled analytical datasets to support reporting, dashboards, experimentation, and data science use cases.
Work closely with analysts and data scientists to understand data requirements and translate them into reliable, reusable data assets.
Monitor data pipelines and datasets, identifying and resolving data quality or reliability issues.
Contribute to data documentation, testing, and basic observability to improve trust and usability of data across the business.
Support the ongoing improvement of Smartly’s data tooling, pipelines, and development practices.
Operate comfortably within a cloud-based environment, with a working understanding of how data systems run in the cloud.

3+ years’ experience in a data engineering, analytics engineering, or similar role.
Strong SQL skills, with experience writing complex and performant queries.
Strong Python skills, particularly for data transformation, automation, and pipeline development.
Experience using Git or similar version control systems in a team environment.
Familiarity with CI/CD practices, including automated testing and deployment workflows.
Working knowledge of cloud infrastructure concepts (e.g. compute, storage, permissions), ideally within a modern cloud platform.
Experience working with relational databases and analytical data stores.
Familiarity with data modelling concepts for analytics (e.g. fact and dimension tables).
Comfortable working hands-on and owning data tasks end-to-end with appropriate support.
Able to collaborate effectively with analysts, data scientists, and software engineers.
Curious and proactive, with a desire to improve data quality and engineering practices.
Clear communicator, able to explain data issues and solutions to both technical and non-technical stakeholders.

Data Engineer

Key skills