Senior Data Engineer
Senior Data Engineer responsible for building scalable ingestion pipelines, normalizing, and maintaining large-scale financial and alternative datasets from global vendors to support quantitative research and alpha generation. Requires 5+ years data engineering experience in finance/quant environments, strong Python/SQL/Linux skills, and deep knowledge of market/tick/reference data across asset classes.
About the job
Responsibilities
- Design, build, and maintain scalable ingestion pipelines for market, reference, tick, and alternative data from a diverse set of external vendors.
- Own the normalization, validation, storage, and lifecycle management of research datasets, ensuring data is accurate, consistent, and readily accessible for quantitative research and simulation.
- Develop and optimize Python- and SQL-based data processing workflows supporting multiple asset classes, including equities, options, futures, fixed income, ETFs, and FX.
- Partner with quantitative researchers, data architects, and infrastructure teams to onboard new datasets, improve data quality, and deliver reliable research-ready data.
- Build monitoring, automation, and operational tooling to ensure the reliability, performance, and scalability of the firm's data platform.
- Document data pipelines and engineering best practices while contributing to the ongoing evolution of Trexquant's research data infrastructure.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
- 5+ years of data engineering experience within a systematic trading, quantitative research, hedge fund, or financial technology environment.
- Python and SQL development experience in building large-scale data ingestion and ETL pipelines.
- Strong Linux experience, including scripting, automation, and operating production data processing systems.
- Deep knowledge of financial data across multiple asset classes, including equities, options, futures, fixed income, ETFs, FX, and alternative datasets.
- Experience working with market data, tick data, reference data, and vendor data feeds, including normalization, validation, and quality control.
- Familiarity with modern data storage formats and technologies such as Parquet, Arrow, object storage, and columnar databases.
- Strong communication and collaboration skills, with the ability to work effectively alongside researchers and engineering teams.
Benefits
- Competitive salary plus bonus based on individual and company performance.
- Collaborative, casual, and friendly work environment.
- PPO health, dental, and vision insurance premiums fully covered for you and your dependents.
- Pre-tax commuter benefits.
- Weekly company meals.
The base salary range is $150,000–$200,000, depending on the candidate's educational and professional background. Base salary is one component of Trexquant's total compensation, which may also include a discretionary, performance-based bonus.
Skills
Python, SQL, Linux, ETL, Parquet, Arrow, Market Data, Tick Data, Financial Data, Data Pipelines, Data Normalization, Data Validation
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