Data Engineer in Plymouth

Data Engineer – HM Land Registry (HMLR)

HM Land Registry (HMLR) is undertaking a large transformation programme to modernise digital systems that support over £7 trillion of property ownership. As a Data Engineer, you will support the development of HMLR’s data engineering capability by building and maintaining reliable data pipelines and products to improve data access, quality and value across the organisation.

Salary up to £44,400 with 29% employer pension contribution and full Civil Service benefits. Flexible, hybrid working from Plymouth, Croydon or Coventry.

Key Responsibilities

• Support the design and maintenance of data flows that connect operational systems and provide data for analytics and BI.
• Help re‑engineer manual processes into scalable, repeatable data pipelines and write optimised ETL code.
• Contribute to building data streaming capabilities and creating accessible data products for analysis.
• Improve data quality, document data mappings and identify opportunities to optimise data engineering processes.
• Work collaboratively with other teams, follow industry best practice aligned to HMLR standards, and participate in the data engineering community.
• Develop understanding of legacy systems, learn the basics of Land Registry operations, and maintain awareness of organisational priorities.
• Continue personal development to build skills and knowledge relevant to the role.

Essential Skills

• Experience of using a unified engine for large-scale data analytics (e.g. Spark/PySpark).
• Experience in writing, testing and implementing scripts (e.g. Python, Scala).
• Experience of cloud data stack use (e.g. SageMaker Notebooks, S3, Glue, Athena).
• Communicating technical concepts clearly to both technical and non‑technical stakeholders.
• Profiling data and analysing source systems to produce clear, actionable insights.

Desirable Skills

• Knowledge of DevOps processes (e.g. Terraform).
• Knowledge of data pipeline testing (end‑to‑end testing, data quality testing, monitoring & alerting, unit & contract testing).
• Knowledge of the data lifecycle (development, analysis, modelling, integration, metadata management).

Location

Expectation is to be working from any of the advertised locations 60% of your time across the month (typically three days per week