£300,000 tc - Data Platform Engineer - Leading Hedge Fund

Saragossa; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Saragossa in London is seeking a data platform engineer to build and own Python-based data pipelines and platform infrastructure at scale. You’ll work with a lean, high-trust data team to turn raw finance and internal data into insights the firm relies on.

You’ll collaborate across Snowflake, Starburst, Airflow, dbt, SQL Server and CubeJS, shaping data modeling, governance and accessibility for stakeholders across the firm.

Qualifications

• Strong Python, with fluent, hands-on pandas or equivalent library.
• Solid SQL and experience owning data systems at scale, from ingestion and orchestration through to modelling and serving.
• A clear grasp of what makes pipelines reliable and platforms maintainable, and the ability to explain the trade-offs behind your decisions to non technical stakeholders.
• Experience with modern orchestration and cloud data tooling. The stack is deliberately agnostic, so how you think about the problems matters more than the specific tools.
• Confidence with senior stakeholders, and genuine enthusiasm for the work, including the curiosity to keep learning outside working hours.

Responsibilities

• Build and own Python-based data pipelines and platform infrastructure at meaningful scale.
• Orchestrate and transform data across a modern stack that currently includes Snowflake, Starburst, Airflow and dbt, alongside SQL Server, with CubeJS serving the semantic layer
• Work across a broad range of data, from finance data to internal business data
• Raise data quality, lineage and accessibility for stakeholders across the firm
• Explain complex technical work clearly and credibly to senior people

Skills

Python

Pandas

SQL

Data pipelines

Data platforms

Orchestration

Cloud data tooling

Stakeholder communication

Tools

Snowflake

Starburst

Airflow

dbt

SQL Server

CubeJS

Job description

Direct access to the top of the firm, sensitive data, and the freedom to shape the platform a leading hedge fund runs on.

You'd be joining one of the most data-driven hedge funds in the industry, in a role that is not typical software engineering. You won't be building transaction systems. You'll be extending a small, high-trust data team (seven people) and building the platform that turns raw finance and internal data into insight the whole firm relies on.

Finance experience isn't required. Backgrounds in data infrastructure, backend systems or other data-heavy industries are welcome, and this is a great way into a lucrative sector while working close to the business.

Why this role is different

• Access. You'll work directly with the top ten people across the firm on a regular basis. In a lean, high-performing fund, that level of exposure is rare.
• Trust. The team looks after some of the most sensitive data in the organisation, so reliability, governance and security are core to the job.
• Ownership. With a team of seven, your work shapes how the platform is designed, how data is modelled and served, and how it scales.
• Freedom. If you spot a better tool or a smarter approach, you can propose it and expect to be heard. Your manager will back you and help you grow.

What you'll do

• Build and own Python-based data pipelines and platform infrastructure at meaningful scale
• Orchestrate and transform data across a modern stack that currently includes Snowflake, Starburst, Airflow and dbt, alongside SQL Server, with CubeJS serving the semantic layer
• Work across a broad range of data, from finance data to internal business data
• Raise data quality, lineage and accessibility for stakeholders across the firm
• Explain complex technical work clearly and credibly to senior people

What we're looking for

• Strong Python, with fluent, hands-on pandas or equivalent library.
• Solid SQL and experience owning data systems at scale, from ingestion and orchestration through to modelling and serving
• A clear grasp of what makes pipelines reliable and platforms maintainable, and the ability to explain the trade-offs behind your decisions to non technical stakeholders
• Experience with modern orchestration and cloud data tooling. The stack is deliberately agnostic, so how you think about the problems matters more than the specific tools
• Confidence with senior stakeholders, and genuine enthusiasm for the work, including the curiosity to keep learning outside working hours