Back to jobs

Senior Data Engineer (Databricks / Snowflake)

London

Pay
Salary not listed in the saved posting
Work setup
Unconfirmed
Employment
Unconfirmed

What you’ll work on

Full posting

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 write code, review architecture decisions, lead junior engineers and explain trade-offs to people who aren't engineers.

  • 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

From the employer’s posting
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.
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
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
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

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • dbt
  • Google Cloud (GCP)
  • Snowflake
  • PySpark
Source — Tool mentions in context
- 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)
- 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
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
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
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
- 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

Benefits in the posting

Full benefits wording
  • Competitive base salary
  • Annual performance bonus tied to individual and company outcomes.
  • Comprehensive benefits package including private medical insurance, life assurance, and income protection.
  • 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.

From the employer’s posting.

Job description

View original posting ↗

 

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 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.

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

London

- 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.
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Jul 12, 2026
Recorded sightings
92
Last seen by us
Oct 9, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.