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.‑service analytics‑governed, and AI‑ready

This is a hands on senior individual contributor role with clear technical leadership expectations. You will own complex data domains and pipelines, set and uphold engineering standards, and mentor other data engineers, while still spending a significant portion of your time building.

Design & Evolve Scalable Data Warehousing Solutions:

• Lead the design, build, and maintenance of robust, well tested ELT / ETL pipelines and transformation workflows‑tested ELT / ETL pipelines and transformation workflows
• Model and maintain curated data layers to support reporting, analytics, and operational decision making‑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

Enable Data Democratisation & Self Service‑Service:

• Design intuitive, well structured data models that power self serve BI (e.g. AWS Quick Sight, SQL export)‑structured data models that power self‑serve BI (e.g. AWS
• 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

Governance, Quality, and Compliance by Design:

• 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 readyby enforcing high standards for data quality, provenance, and documentation, so they can safely power analytics, machine learning, and future AI use cases‑ready

Technical Leadership &

Collaboration:

• 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 significant 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 inSQL & Python for data processing, orchestration (e.g. Airflow MWAA), and…