Data Engineer

LHV Bank, a fully licensed UK bank, specialises in Savings, Banking Services for global fintechs, and SME Lending solutions for UK businesses, offering commercial real estate investment and trading loans from £0.5m. As a leading provider of real-time multi-currency payments, accounts, acquiring, indirect scheme access, open banking, and FX solutions, LHV Bank supports 200+ fintech companies, including Airwallex, Currencycloud, Truelayer, and Wise, serving 10 million+ end customers and reaching a potential market of 500 million across the UK and Europe.

After obtaining its UK banking licence in May 2023, LHV Bank entered the retail savings market via deposit aggregators in August 2023, followed by the launch of its direct-to-customer retail banking proposition in December 2024.

For more information, visit lhv.com.

We are seeking a skilled Data Engineer with a strong focus on modern data warehousing, data product development, and data democratization. You will play a key role in designing, building, and optimizing scalable data pipelines and clean data layers that empower teams across the organization to make informed, data-driven decisions.

This is a hands-on role that blends engineering excellence with product thinking, metadata management, and a passion for enabling self-service analytics and data literacy across the business.

Key Responsibilities:

 Build & Maintain Scalable Data Warehousing Solutions:

• Design, build, and maintain robust ELT pipelines and transformation workflows
• Model and maintain curated data layers to support reporting, analytics, and decision-making
• Ensure high availability, scalability, and performance of data warehouse systems (cloud-based, e.g., Redshift)

Develop & Manage Data Products:

• Collaborate with business and domain experts to define and deliver high-value, reusable data products
• Implement best practices around versioning, SLAs, data contracts, and quality validation
• Own the end-to-end lifecycle of key datasets, including documentation, testing, monitoring, and maintenance
• Use metadata, lineage, and usage metrics to ensure data products are trustworthy, discoverable, and valuable

Enable Data Democratization & Self-Service:

• Build intuitive, well-structured data models to empower BI tools (e.g., QuickSight, Power BI, Tableau)
• Collaborate with analysts and domain users to promote adoption of self-serve analytics tools
• Create and maintain data dictionaries, technical and business catalogs, and user onboarding documentation
• Contribute to internal data enablement initiatives such as training and knowledge-sharing sessions

Governance, Quality, and Compliance:

• Implement data access controls and support zero-trust security principles
• Support data classification, lineage, and automated data governance tooling
• Ensure compliance with internal and external data policies (e.g., GDPR)

What We’re Looking For

Essential:

• 3+ years of experience as a Data Engineer, with a strong focus on data warehousing and data modeling
• Hands-on experience with cloud-native data tech (preferably AWS: Redshift, Glue, S3, Lambda, IAM, Terraform, GitHub, CI/CD)
• Proficiency in SQL and Python for data processing and automation
• Experience working with data modeling tools and practices (e.g., dimensional, star/snowflake schema, dbt)
• Solid understanding of data governance, metadata, and quality frameworks
• Strong collaboration and communication skills, with the ability to work cross-functionally in an Agile environment

Desirable:

• Exposure to data product management principles (SLAs, contracts, ownership models)
• Familiarity with orchestration tools and observability platforms (Airflow, dbt, Monte Carlo, etc.)
• Exposure to real-time/streaming pipelines
• Understanding of information security best practices
• Familiarity with BI tools (QuickSight, Power BI, Tableau, Looker, etc.)
• Interest or experience in building internal data communities or enablement programs
• Working with diverse data sources (APIs, CRMs, SFTP, databases) and formats (Parquet, JSON, XML, CSV)
• Exposure to machine learning models or AI agents

Why Join Us

• Help shape the future of data in an organization that treats data as a product
• Work in a modern data stack environment with a focus on real impact
• Be part of a collaborative, open, and empowering data culture
• Drive innovation in self-service analytics and data literacy