Senior 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 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 Our senior data engineers are hands-on leaders of consultants and client teams, building data platforms for clients in regulated financial services – private equity, real estate, fund administration, and specialist insurance. You'll work directly with client stakeholders, from engineering leads to CTOs, delivering production pipelines on Databricks or Snowflake (strong experience in one is sufficient). This is a hands-on build role with client exposure. You'll write code, review architecture decisions, lead junior engineers and explain trade-offs to people who aren't engineers. What you'll do Lead and mentor junior engineers on your delivery workstream, reviewing their code and data model decisions Build reliable ingestion pipelines that move client data from source systems into the platform efficiently and securely Design data models – Data Vault 2.0, Kimball Dimensional etc. that survive audit and give the business one trusted version of the numbers Build pipelines to agreed SLAs and own their reliability in production Work with domain SMEs to translate business logic into pipeline logic that produces correct numbers Bring LLM-based processing into pipelines where it fits, document parsing, entity extraction, unstructured data classification, alongside deterministic logic Build AI-powered business solutions on the platform, agents, search, and applied use cases on Mosaic AI or Cortex, that solve a client problem with trusted data rather than demo a capability Support pre-sales by sizing effort and cost for prospective engagements, contribute to delivery plans, and present technical approach to prospective clients What you'll bring 4+ years in data engineering, with at least 2 years on Databricks or Snowflake in production (one platform is sufficient) Strong SQL and Python; comfort with PySpark or Snowpark Strong experience with at least one cloud vendor, Azure, AWS, or GCP, including core services beyond the data platform itself (networking, IAM, storage) Working knowledge of dimensional modelling (Kimball) and/or Data Vault 2.0 Comfortable presenting technical decisions to non-technical stakeholders Track record of setting engineering standards and reviewing others' code for quality, not just correctness Comfortable leading or mentoring junior engineers on a delivery team, and taking ownership of technical decisions Additional experience we’d value Snowflake or Databricks certifications Familiarity with private markets data (fund administration, private equity/real estate, secondaries) or London Market insurance Experience with supporting tooling such as IaC; Transformation (dbt); DevOps; Data Quality; Data Modelling; Data Glossary/Governance; iPaaS/ELT, Orchestration Some exposure to regulated environments – financial services, insurance, or similarly audited sectors – and awareness of relevant regulatory frameworks including FCA SYSC, DORA, and MiFID II What the engagement looks like You'll work closely with client teams, alongside their internal engineers and Alpha consultants in a regulated environment where change control, data lineage and documentation matter. You'll write code, typically tackli…