Senior Data Engineer - Up to £100,000 base salary - Private Equity

Saragossa; Greater London; Vor Ort; GBP 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Competitive base salary

Discretionary annual bonus

Long-term share incentive plan

Generous pension

Private medical cover

15 work from anywhere days

Zusammenfassung

Saragossa in London is seeking an experienced Data Engineer to design and build a governed, scalable data platform for reporting, analytics, and AI. You will select and prove the stack, starting with a Databricks on Azure PoC, then shape the architecture, codebase and delivery while growing ownership of the platform.

You will implement ingestion pipelines, Terraform and CI/CD from day one, add lineage and Unity Catalog, and enable BI and AI-ready datasets for the board.

Qualifikationen

• 5 to 7 years of hands-on data engineering, including at least 3 as a core engineer on a significant platform build in investment management or financial services.
• Strong SQL, Python and Spark, plus lakehouse, data modelling and governance experience.
• Hands-on work applying LLMs to data, production or serious side projects; experience with private markets data, Databricks, Power BI or Terraform; Snowflake ok.

Aufgaben

• Design and build a governed data platform for reporting, analytics and AI.
• Write ingestion pipelines for multiple sources and implement a medallion lakehouse.
• Set up Terraform, CI/CD from day one and Unity Catalog for data lineage.
• Enable Power BI and Databricks SQL-based data access for investment teams.

Kenntnisse

SQL

Python

Spark

Data modelling

Governance

LLMs in data

Ingestion pipelines

Tools

Databricks

Power BI

Terraform

CI/CD

Unity Catalog

Azure

Snowflake

Jobbeschreibung

It’s a Monday morning. A Board pack goes out on Thursday, and somewhere among an IBOR, a stack of custody files, a risk feed, a private markets capital call notice and a few dozen spreadsheets are the numbers that will end up in it. Today, a small team of people pull them together by hand.

That’s about to change, and you’d be the one changing it.

Our client is a long-established London investment firm managing a multi-billion pound, multi-asset portfolio across quoted equities, public and private funds, direct holdings, credit and currencies. Their senior leadership has backed a single ambition: one trusted, governed data platform for reporting, analytics and, in time, AI.

There’s no legacy platform to inherit and no design handed down from above. You’ll start by helping choose and prove the stack, beginning with a Databricks proof of concept on Azure. Then the architecture, the codebase and the delivery are yours. You’ll build a medallion lakehouse around the core investment domains: security master, positions, transactions, performance and private markets. You’ll write ingestion pipelines for every source, put Terraform and CI/CD in place from day one, and add lineage, quality checks and Unity Catalog so that any number reaching the Board can be traced back to where it came from.

Then the next chapter begins. New risk and private markets systems will arrive, and you’ll bring each one in faster than the last. The investment and finance teams will start exploring data for themselves through Power BI and Databricks SQL. The firm already uses frontier AI models, and you’ll build the AI‑ready datasets and RAG retrieval over NAV statements and capital call notices that take that further.

You’ll report to the Head of Technology, work alongside a junior data engineer and become the firm’s go‑to authority on its data. The role stays hands‑on with no line management. You grow by owning more of the architecture over time.

You’ll probably have:

5 to 7 years of hands‑on data engineering, including at least 3 as a core engineer on a significant platform build in investment management or financial services. You’ll bring strong SQL, Python and Spark, along with lakehouse, data modelling and governance experience. Hands‑on work applying LLMs to data, whether in production or in serious side projects, will set you apart. It helps if you’ve worked with private markets data, Databricks, Power BI or Terraform. Also, happy to look at candidates with Snowflake experience.

In return:

a competitive base salary, a discretionary annual bonus and a long‑term share incentive plan. Benefits include a generous non‑contributory pension, family private medical cover and 15 “work from anywhere” days a year.

If you’ve built a platform under a lead and now want to make the architectural calls yourself, this is where your story continues.