Data Engineer

Job Description: Data Engineer – Global Data Platform About the Company We are a leading global multi-strategy hedge fund with a strong presence across major financial centers. Our firm is committed to delivering superior risk-adjusted returns to our investors through innovative strategies and a disciplined approach to risk management. Our teams thrive on collaboration, innovation, and leveraging data as a competitive edge. Role Overview As a Data Engineer, you will be a member of the team responsible for delivering the data that enables the growing number of portfolio managers to research, test, execute and manage their investment strategies with ease and confidence, which is crucial to the firm’s success and growth. You will be designing, implementing, and maintaining scalable and robust data pipelines and frameworks that deliver lasting value for portfolio managers, Quants and risk managers by enabling them to onboard new data and use-cases quickly and with robust quality checks. You have worked in or with financial industry Front Office businesses. You care about data quality, testing, performance, are curious and have a methodical approach to ensure that you fully understand the business needs and potential impact of operational issues. You use this to identify appropriate technical solutions leveraging the global data platform where possible, and raise gaps to the Data Platform team when the solution requires a non-platform component. Responsibilities: Implement customer-centric data solutions: Collaborate with customers to understand their specific needs, and translate them into robust, scalable data solutions that satisfy the pace demanded by hedge fund operations. Typically some combination of onboarding new financial data sets, implementing data pipelines & external connectors as necessary, along with automated tests for each component as early in the development process as possible. Implement automated Data Quality checks at every step of the development & data life cycle to ensure the accuracy, reliability, quality and robustness of data with very high confidence. Automate monitoring and alerting to enable the DataOps team to proactively resolve any issues 24/7 with minimal business impact. Integrate with vendor & platform systems: Manage data feed integration with external vendor sources with a focus on fast onboarding and rigorous data validation, as well as with internal 3rd party trade and position keeping & risk systems, and the firm’s central Data Platform. Contribute to platform development: Identify recurring patterns in customer needs, propose and implement configurable frameworks. Ensure sufficient process telemetry data allows observation of potential bottlenecks or issues to ensure high availability, robustness and performance. Role-model continuous improvement: Maintain high standards of technical excellence, ownership and customer care. Mentor junior engineers and help hire new talent. Streamline workflows, improve data quality, and efficiency to support faster insights and improved decision-making by our customers. Qualifications & Experience: BSc/MSc/PhD in Computer Science, Physics, Engineering or similar and 5 years financial industry experience in Front Office Tech / Quant organizations or Data Platform Technology, preferably with some time spent in a hedge fund. Technical Hands-on experience with cloud platforms such as AWS, Google Cloud, or Azure, and corresponding data storage and processing services, e.g. AWS RDS (postgres), S3, MSK (Kafka). Strong proficiency in Linux environments. Advanced SQL skills and experience with modern data storage & querying technologies (e.g. Snowflake, Redshift, BigQuery), and file formats (e.g. Parquet and Iceberg) Proficiency programming in Python and familiarity with Pandas data frames. Experience of high throughput & low latency programming in languages such as Python, C#, F#, C or Java is a plus. Demonstrated experience in test automation to maintain high standards and a fast rate of change with confidence, preferably have used DBT. Familiarity with monitoring production systems using modern observability solutions (e.g. Grafana/Prometheus, DataDog, ELK). Hands-on experience with data pipeline orchestration tools, e.g. Airflow, and data download mechanisms, e.g. sFTP, various vendor APIs. Proficiency in integrating with 3rd-party data providers and vendor APIs typical in hedge funds would be ideal. Financial Data: Familiarity with at least some market and reference data, ideally across a broad range of asset classes, hedge fund data workflows (sourcing, processing, analysis), real-time data needs, and financial compliance considerations (e.g. licensing, access control). Soft Skills: Effective communication skills with Front Office stakeholders and Tech colleagues, curiosity, a collaborative mindset, ability to produce in an agile environment. We are a global investment management firm.