Principal Data Engineer
Summary
Lead the evolution of Companies House's cloud data platform, setting engineering standards and building analytical foundations on Snowflake and dbt. The role blends hands-on data engineering design with mentoring engineers, owning the platform roadmap, and influencing senior stakeholders to drive organisation-wide data adoption.
In this role you will lead the evolution of Companies House's cloud data platform, shaping data services at scale. You will guide cross-functional teams, set engineering standards, and turn data into a strategic asset across the organisation. You will influence senior stakeholders, drive technology roadmaps, and deliver measurable data outcomes for users and the business. The position centers on building a platform with Snowflake and dbt to underpin analytical products and drive organisation-wide adoption. You will mentor engineers and champion modern engineering practices to support a data-driven culture.
Pay / Benefits- Flexible working with hybrid options
- 30 days annual leave
- 8 bank holidays plus privilege day
- Civil Service Pension scheme
- funded training and professional qualifications
- career progression opportunities
- Shape the strategic direction and evolution of the data platform to deliver long-term value and drive adoption
- Lead design, development and optimisation of scalable data engineering solutions and trusted datasets
- Provide technical leadership, establish standards and best practices for quality, automation, security and reliability
- Drive continuous improvements in data architecture, processes, performance and operations
- Maintain governance, documentation and knowledge sharing to support continuity and compliance
- Build relationships with senior stakeholders to promote data-driven decision making
- Coach and develop a team of data engineers, fostering an inclusive, high-performing culture
- Manage performance, resource planning and capability development to meet current and future needs
- Experience establishing data engineering best practices (coding standards, automation, testing, reproducibility, quality assurance, continuous improvement)
- Advanced SQL and practical experience with Python, Git, dbt, Snowflake, Databricks or comparable technologies
- Strong data modelling knowledge (Kimball methodologies, star schemas, fact/dimension modelling, slowly changing dimensions)
- Ability to own a data product/platform/service and shape its strategy and roadmap
- Commitment to fostering an inclusive, collaborative, high-performing team culture
- leadership
- stakeholder influencing
- collaboration
- SQL
- Python
- Git