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 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 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.

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 tackling the most complex challenges, review code and data model decisions across the team, and take responsibility for a delivery workstream – planning it, running it, and leading the junior engineers working on it.

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.