At a Glance
- Tasks: Design and build a modern data platform, ensuring data quality and governance.
- Company: LHV Bank, a UK-licensed bank with a focus on innovation and fintech.
- Benefits: Competitive salary, hybrid working, health plans, and generous holiday allowance.
- Other info: Join a collaborative team with opportunities for professional growth.
- Why this job: Shape the future of data at a growing bank and make a real impact.
- Qualifications: Experience in data engineering, Python, and cloud technologies required.
The predicted salary is between 48000 - 72000 € per year.
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. 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.
Key Responsibilities- Design, build, and maintain 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 QuickSight, SQL exports).
- Partner with analysts and domain teams to make data products 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.
- 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 in SQL & 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, GitHub Actions, CodeBuild/CodePipeline).
- 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 needs, and to mentor more junior team members.
- Experience designing and operating data products with clear SLAs, contracts, and ownership models.
- Hands-on experience with orchestration and observability tooling (e.g. Airflow, Step Functions, dbt, Coralogix).
- Exposure to real-time / streaming data pipelines (e.g. Kinesis, Kafka, MSK) and understanding of information security best practices in regulated environments.
- Familiarity with BI and analytics tools (e.g. QuickSight) and how engineers can enable them effectively.
- Experience working with diverse data sources (APIs, CRMs, SFTP, relational/NoSQL databases) and formats (Parquet, JSON, XML, CSV).
- Experience contributing to internal data communities, guilds, or enablement programmes.
- Experience with financial data or working in financial services / other regulated industries.
Play a key role in shaping our data platform and practices, working directly with the Head of Data & AI in a wider Data & AI team. Work with a modern data stack and have real influence over the tools, patterns, and standards we adopt. Help build and scale a culture that treats data with importance, with strong focus on data trust, quality, governance, and usability. Make a visible impact by enabling self-service analytics, data literacy, and better decision making across the organisation.
Some Of Our Benefits- Competitive salary & lots of opportunities to learn, grow and progress professionally.
- Open and inclusive culture.
- Hybrid working.
- Fantastic offices and great working environment.
- Vitality Health Plan (includes private health insurance, travel insurance, gym discounts).
- Health cash Plan (Medicash health plan Level 3).
- 5% employer pension contribution.
- Life assurance – 4 x salary.
- Income protection insurance – 75%.
- 28 days holiday plus 3 additional days, and further days for various key life events as well as the opportunity to sell up to 5 days per calendar year.
- Swap public/bank holidays each year for alternative days that align with your personal, cultural, or religious observances.
- Enhanced family friendly and family forming policies.
- Access to a wide range of retail discounts.
- Team Socials.
Senior Data Engineer in Leeds employer: LHV Bank
LHV Bank Limited is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a Senior Data Engineer, you will have the opportunity to shape our modern data platform while enjoying a competitive salary, hybrid working options, and a strong focus on professional growth. With a commitment to inclusivity and employee well-being, LHV Bank provides comprehensive benefits including health plans, generous holiday allowances, and a vibrant office culture that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in Leeds
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those that highlight your experience with cloud technologies and data modelling. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team at LHV Bank.
We think you need these skills to ace Senior Data Engineer in Leeds
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with cloud data technologies and data modelling, as these are key for us. Use specific examples that showcase your skills in Python and SQL.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're the perfect fit for LHV Bank. Share your passion for data engineering and how you can contribute to our data platform. Don't forget to mention any relevant projects or achievements!
Showcase Your Technical Skills:In your application, be sure to highlight your hands-on experience with tools like dbt, Airflow, and AWS services. We want to see how you've used these technologies to solve real-world problems, so give us the details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen on joining our team!
How to prepare for a job interview at LHV Bank
✨Know Your Data Tools
Make sure you’re well-versed in the specific data technologies mentioned in the job description, especially AWS tools like Redshift and Glue. Brush up on your Python and SQL skills, as you'll likely be asked to demonstrate your proficiency during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past projects where you designed and built data pipelines or models. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will show your ability to lead complex data solutions.
✨Understand Data Governance
Familiarise yourself with data governance principles, including data quality and lineage. Be prepared to discuss how you’ve implemented these in previous roles, as this is crucial for maintaining compliance and trust in data.
✨Communicate Effectively
Practice explaining technical concepts in simple terms, as you’ll need to bridge the gap between technical details and business needs. Highlight any mentoring experience you have, as this role involves guiding junior team members.