Data Engineer (Databricks / Snowflake)

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 by focusing across the General Insurance & Specialty value chain, we build deep knowledge and experience within our industry. 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.

The Insurance team works with industry leading carriers, brokers, market bodies, ancillary businesses, and technology providers to position our clients for future success. We have a fast growing team of dedicated consultants with deep experience from working both within the industry and consulting. Successful candidates should expect a diverse range of complex and strategic engagements across the market. As we continue to expand our client base and expertise, we are looking for individuals to join our team to support our growth journey. Please see below an outline of the responsibilities of the role as well as the requirements.

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.

• →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
• →Work on delivery teams building AI-enabled solutions on the platform, helping to apply trusted data to real client problems
• →Share learnings from delivery work and contribute to internal assets, tooling, and practices over time.

• 2+ years in data engineering, including production experience with Databricks or Snowflake (one platform is sufficient)
• Strong SQL and Python; comfort with PySpark or Snowpark
• Experience with at least one cloud vendor, Azure, AWS, or GCP, including familiarity with core services beyond the data platform itself (networking, IAM, storage)
• Working knowledge of dimensional modelling (Kimball) and/or Data Vault 2.0
• Strong attention to quality, documentation, and delivery discipline

• Snowflake or Databricks certifications
• Familiarity with private markets data (fund administration, private equity/real estate, secondaries) or London Market insurance
• Experience with some supporting tooling across areas such as infrastructure-as-code, transformation, DevOps, data quality, governance, or orchestration would be beneficial.
• Exposure to regulated environments such as financial services, insurance, or similarly audited sectors would be beneficial.

You'll work within client teams, alongside their internal engineers and Alpha consultants in a regulated environment where change control, data lineage and documentation matter. Expect a mix of independent build work and collaborative delivery, with regular touchpoints against a delivery plan.