Data Engineer (Databricks / Snowflake)

Job description

Alpha Financial Markets Consulting (Alpha) is a leading global consultancy to the financial services industry. We are a boutique management consulting firm that offers the world’s top industry players a competitive edge through our expertise and industry insight. Our team is of a uniquely high calibre and works across regulated financial markets, bringing deep expertise in insurance, alternative asset markets — including private equity, private credit, infrastructure and real estate — and other specialised financial sectors. This focus enables us to bring relevant, hands-on experience to our clients’ most important challenges. We have our headquarters located the United Kingdom, as well as offices in major global financial centres across the United States, France, Netherlands, Luxembourg, Switzerland, and Asia. About the role We’re looking for a Data Engineer with 2+ years’ experience to join our growing data engineering capability. This role is focused on client delivery. You’ll work closely with client teams, alongside their internal engineers and Alpha consultants, to build and support modern data platforms in regulated financial services environments. The work is hands-on and delivery-focused: building pipelines, developing data models, and helping turn business requirements into trusted, production-ready data solutions. This is a strong opportunity for an engineer who wants more than just pipeline delivery. You’ll work directly with clients, solve real platform and data problems, and build experience across a range of delivery challenges in complex regulated environments. What you'll do Build reliable ingestion pipelines that move client data from source systems into the platform efficiently and securely Develop data pipelines to agreed SLAs, with a focus on reliability in production Work with domain SMEs and delivery teams to translate business logic into pipeline logic that produces accurate, trusted outputs Senior Data Engineer.docx Design data models, including Data Vault 2.0 and Kimball dimensional models, that support auditability and trusted reporting Support testing, monitoring, troubleshooting, and documentation across the delivery lifecycle Contribute to engineering standards and delivery best practices as part of a wider team Work with the team to implement LLM-based processing in pipelines where appropriate, alongside deterministic logic Wo…