Senior Data Engineer

LHV Bank Limited is a UK‑licensed bank operating across three core business segments:
Retail Banking, SME Lending, and Banking Services (BaaS). The bank is a wholly owned subsidiary of LHV Group, a listed financial services provider headquartered in Estonia. LHV Bank operates under a full UK banking licence granted in May 2023. The Bank supports over 200 fintech clients with embedded financial infrastructure, provides retail savings products via digital channels, and offers SME credit solutions across the UK.

In line with its regulatory responsibilities and growth ambitions, LHV Bank is committed to maintaining a robust and proportionate financial crime control environment. Expanding our services, LHV Bank now provides personal banking solutions. Our offerings include current accounts with competitive interest rates, fixed‑rate bonds for long‑term savings, and debit cards. Customers can conveniently access these services through the LHV App, enabling secure account opening and management.

We are looking for an experienced Senior Data Engineer to help design, build, and evolve our modern data platform. You will shape our data warehousing, data products, and self‑service analytics, ensuring our data is trusted, well‑governed, and AI ready, working closely with the Head of Data & AI and the wider Data & AI team.

• Lead the design, build, and maintenance of robust, well‑tested ELT/ETL pipelines and transformation workflows.
• Model and maintain curated data layers to support reporting, analytics, and operational decision making.
• Optimise the performance, reliability, and cost of our cloud data warehouse.
• Contribute to data architecture decisions, patterns, and standards in partnership with the Head of Data & AI.
• Design intuitive, well‑structured data models that power self‑serve BI (e.g., AWS Quick Sight, SQL export).
• Partner with analysts and domain teams to make data products genuinely usable and widely adopted.
• Contribute to data enablement initiatives such as training sessions, playbooks, and internal documentation.
• Help develop and maintain data dictionaries, business glossaries, and technical catalogues.
• Embed data quality checks, alerts, observability, and access controls into pipelines and data products from the outset.
• Support data governance capabilities (classification, lineage, audit, retention) using automated tooling where possible.
• Work closely with risk, security, and compliance stakeholders to ensure adherence to internal and external requirements (e.g., GDPR).
• Ensure our core data assets are AI ready by enforcing high standards for data quality, provenance, and documentation, so they can safely power analytics, machine learning, and future AI use cases.
• Provide technical guidance and code review for other data engineers, helping to raise the bar on quality and reliability.
• Contribute to shared engineering practices (coding standards, testing strategy, CI/CD, observability).
• Collaborate in an agile environment with product, analysts, and stakeholders to break down work and deliver iteratively.
• Help evaluate and introduce new tools, patterns, and approaches to improve our data platform over time.

• Significant experience as a Data Engineer (or similar role), including experience in Python, cloud data warehousing, and data modelling (dbt).
• Strong hands‑on experience with cloud native data technologies, preferably on AWS (e.g., Redshift, Glue, S3, Lambda, IAM).
• Proficiency in SQL and Python for data processing, orchestration (e.g., Airflow MWAA), and automation.
• Experience with modern transformation and modelling approaches and tools (e.g., dbt, dimensional modelling, star/schema, snowflake).
• Practical experience with infrastructure as code and CI/CD (e.g., Terraform, Git Hub Actions, Code Build/Code Pipeline).
• Solid understanding of data governance, metadata, lineage, and data quality frameworks, and how to implement them in practice.
• Demonstrated ability to lead the design and delivery of complex data solutions, working cross‑functionally in an agile environment.
• Strong communication skills, with the ability to translate between technical details and business…