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
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
- 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.
What you'll bring
- 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
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 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.
What the engagement looks like
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.
What We Offer
- Competitive base salary
- Annual performance bonus tied to individual and company outcomes.
- Comprehensive benefits package including private medical insurance, life assurance, and income protection.
- Hybrid working model with flexible arrangements to support work-life balance.
- Generous pension scheme with enhanced employer contributions.
- Continuous learning budget and access to industry conferences, certifications, and training programmes.
- 25 days annual leave plus bank holidays, with option to buy additional days.
- Employee assistance programme and wellbeing support.
As published by greenhouse
First Name, Last Name, Email, Phone, Resume/CV, Location
- Please confirm if you have at least 2+ years in data engineering, including production experience with Databricks or Snowflake? choose one
- Do you have experience coding with Strong SQL and Python and are comfortable with PySpark or Snowpark choose one
- Do you have experience with at least one cloud vendor, Azure, AWS, or GCP, including familiarity with core services beyond the data platform itself (networking, IAM, storage) choose one
- Dop you have a working knowledge of dimensional modelling (Kimball) and/or Data Vault 2.0? choose one
- Do you have experience of working in the Financial Services Sector? E.g: Banks, Investment firms, Insurance firms? choose one
- Please confirm if you will be able to be based in London for this position? choose one
- Do you currently have the legal right to work in the location you are applying for? choose one
- Please can you confirm what right to work you currently hold? E.g. British Passport, ILR
- Will you at any point in the future require sponsorship to be able to work in this location? choose one
- Please confirm the length of your notice period in your current role?
- Please provide an overview of your current compensation (base salary and details on bonus/benefits)?
- Please provide details on your expectations for compensation for this role (base salary and details on benefits)?