Data Engineer in City of London

Winton is a research-based investment management company with a specialist focus on statistical and mathematical inference in financial markets. The firm researches and trades quantitative investment strategies, which are implemented systematically via thousands of securities, spanning the world's major liquid asset classes. Founded in 1997 by David Harding, Winton today manages assets for some of the world's largest institutional investors. We employ ambitious professionals who want to work collaboratively at the leading edge of investment management.

As a Data Engineer within our Quantitative Platform team, you will play a pivotal role in building and maintaining the data infrastructure that fuels our research and trading strategies. You will be responsible for the end-to-end lifecycle of diverse datasets - including market, fundamental, and alternative sources - ensuring their timely acquisition, rigorous cleaning and validation, efficient storage, and reliable delivery through robust data pipelines.

Responsibilities:

• Evaluating, onboarding, and integrating complex data products from diverse vendors, serving as a key technical liaison to ensure data feeds meet our stringent requirements for research and live trading.
• Designing, implementing, and optimizing robust, production-grade data pipelines to transform raw vendor data into analysis-ready datasets, adhering to software engineering best practices and ensuring seamless consumption by our automated trading systems.
• Engineering and maintaining sophisticated automated validation frameworks to guarantee the accuracy, timeliness, and integrity of all datasets, directly upholding the quality standards essential for the efficacy of our quantitative strategies.
• Providing expert operational support for our data pipelines, rapidly diagnosing and resolving critical issues to ensure the uninterrupted flow of high-availability data powering our daily trading activities.
• Participating actively in team rotations, including on-call schedules, to provide essential coverage and maintain the resilience of our data systems outside of standard business hours.

What we are looking for:

• 5+ years' experience building ETL/ELT pipelines using Python and pandas within a financial environment.
• Prior experience working with equity data and resolving associated challenges, including cross-reference management across multiple vendors, corporate action handling, and revision workflows.
• Familiarity with various technologies such as S3, Kafka, Airflow, Iceberg.
• Proficiency working with large financial datasets from various vendors.
• A commitment to engineering excellence and pragmatic technology solutions.
• A desire to work in an operational role at the heart of a dynamic data-centric enterprise.
• Excellent communication and collaboration skills, and the ability to work in a team.

What would be advantageous:

• Strong understanding of financial markets.
• Experience working with hierarchical reference data models.
• Proven expertise in handling high-throughput, real-time market data streams.
• Familiarity with distributed computing frameworks such as Apache Spark.
• Operational experience supporting real time systems.

We are proud to be an equal opportunity workplace. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.