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.
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Senior Data Engineer - Up to £100,000 base salary - Private Equity employer: Saragossa
Saragossa is an exceptional employer located in the vibrant city of London, offering a dynamic work culture that fosters innovation and collaboration. As a member of our team, you'll enjoy meaningful growth opportunities while working on cutting-edge ML-driven projects that directly impact our research platform. With a focus on real ownership and a clean-slate environment, we empower our employees to turn ideas into actionable strategies, making your contributions truly valuable.
