Senior Data Engineer (Databricks / Snowflake)
Alphafmcroles · London
What this role requires
4 requirements, read out of the advert rather than guessed from the job title:
Also mentioned, not required: PySpark, Snowpark, Azure, AWS, GCP, Data Vault 2.0, Kimball. Worth having, but their absence is not what gets a CV filtered out.
See how often each of these is required across open data roles in Europe.
Free, no card. Tells you which of them your CV evidences and which it only implies.
Job description
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
Read the full description (32 more sections)Show less
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.
Find Jobs in United Kingdom on Arbeitnow
You will apply. Then you will hear nothing.
And no one will tell you what was wrong. See it before you send: your ATS score, every weak line, and the fix for each.
- 1
Drop in your CV
One PDF, thirty seconds. No card.
- 2
See what is wrong with it
Every weak passage, quoted from your own CV, with the line to replace it.
- 3
Apply where you fit
Every European role ranked against what your CV actually says.
- Free, no card
- Your CV file is deleted after parsing
- Or skip the upload — build your profile by hand
- Refreshed every 6 hours