Senior Research Engineer (Data)
Citadel SecuritiesAbout the Role
Data Research Engineers in Citadel Securities are responsible for the curation of large-scale structured and unstructured data and for data assimilation across a multitude of sources. They focus on translating high-level conceptual queries to efficient back-end queries on extremely large-scale data collections, supported by state-of-the-art cloud-based services. The advanced queries enrich alpha signals for the multi-billion-dollar Systematic Business and research function.
- Design, create, automate, and maintain custom data pipelines
- Extract, clean, normalize, and transform raw data while handling edge cases
- Develop high-performance schemas and queries with data validation checks and alerts
- Load processed datasets in formats suitable for quantitative researchers and models
- Develop tooling and analytical infrastructure for pipeline monitoring and data exploration
- Partner with QR teams and business operations to identify and evaluate promising datasets globally
Responsibilities
- Act as data owner of several datasets each with its own unique schema and delivery frequency
- Partner with researchers to produce high-value datasets
- Design, create, automate, and maintain custom data pipelines
- Extract the raw data
- Clean and normalize the data
- Translate high-level market research concepts into scalable processes that further transform the data
- Handle all edge cases
- Develop high-performance schemas and queries
- Setup "data checks" and alerts to determine when the data is "bad"
- Load the processed dataset to a format easily digested by quantitative researchers and models
- Develop tooling to facilitate the development and monitoring of custom data pipelines
- Setup analytical infrastructure to facilitate exploration and visualization of datasets
- Large scale cloud development of applications as a service
Requirements
- Demonstrated experience driving meaningful business outcomes through data engineering
- Prior ownership of a data project or large part of it
- Strong attention to detail
- Good analytical and quantitative abilities
- Demonstrated ability to quickly learn new technologies and skills
- Experience with ETL development
- Experience with data manipulation and query design and optimization
- Experience in time series forecasting and machine learning techniques
- Strong data science skills
- Proficiency in Python
- Experience with SQL databases
- Experience with cloud platforms
- Experience with schedulers
- Experience with containers
- Experience with CI/CD
- Experience with software packaging
- Strong ability to communicate with stakeholders (data vendors, QRs, etc.)
- Experience with Data Build Tool (DBT)
- BS degree in Computer Science, Mathematics, or related Computer Engineering or Science curriculum