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.