- Build and maintain market, economic, research, news, and internal data pipelines, as well as Fenics/BGC data integration.
- Design and implement a scalable bronze/silver/gold data architecture to support our AI and quant models.
- Establish and monitor data quality gates to ensure data integrity and accuracy.
- Develop and manage instrument, ticker, country, client, source, and theme metadata for effective data categorization and retrieval.
- Create APIs and tables for seamless integration with agent tools, dashboards, and quant models.
- Implement data lineage tracking, user entitlements, and permissions management systems.
- Monitor and optimize data pipelines for performance and efficiency, ensuring smooth data flow.
- Collaborate with data scientists and analysts to understand their data needs and provide model-ready datasets.
- Stay updated with the latest trends in time-series and complex-data analysis, incorporating best practices into our data platform.
- Ensure data security and privacy compliance, adhering to industry standards and regulations.
- Strong proficiency in Python and SQL, with experience in production-level ETL/ELT processes.
- In-depth knowledge of cloud data stack technologies, such as Azure, Databricks, Delta Lake, or Snowflake.
- Experience with time-series data and complex data structures, demonstrating an understanding of data quality and monitoring.
- Ability to clean and transform messy data into structured, model-ready datasets, ensuring data integrity.
- Familiarity with ticker-level data processing, having worked with kdb+ or similar systems is an advantage.
- Excellent problem-solving and analytical skills, with a keen eye for detail and data accuracy.
- Strong communication and collaboration skills, able to work effectively with cross-functional teams.
- A proactive and self-motivated approach to work, with a passion for data engineering and continuous improvement.
- A bachelor's degree in Computer Science, Engineering, or a related field is preferred.
- 2+ years of relevant work experience in data engineering or a similar role.
Skills Required
- Strong proficiency in Python and SQL
- Experience with production-level ETL/ELT processes
- Knowledge of cloud data stack technologies such as Azure, Databricks, Delta Lake, or Snowflake
- Experience with time-series data and complex data structures
- Understanding of data quality and monitoring
- Ability to clean and transform messy data into structured, model-ready datasets
- Experience with ticker-level data processing
- Familiarity with kdb+ or similar systems
- Excellent problem-solving and analytical skills
- Strong communication and collaboration skills
- Proactive and self-motivated approach to work
- Bachelor's degree in Computer Science, Engineering, or a related field
- 2+ years of relevant work experience in data engineering or a similar role
What We Do
Cantor Fitzgerald is a leading global financial services firm, serving clients from over 30 offices around the world. Founded in 1945 as a securities brokerage and investment bank, the firm pioneered computer-based bond trading, built one of the broadest distribution networks in the industry and became the market’s premier dealer of government securities. Today, Cantor Fitzgerald is known for its strength across a diverse array of businesses, including equity and fixed income capital markets, investment banking, commercial real estate finance and services, prime brokerage, asset management and wealth management, and e-commerce and online ventures. In all its businesses, the firm is an acknowledged leader in developing advanced technologies to expand market access, and help clients achieve their most important financial and strategic objectives. This commitment to client-centered innovation has led to enduring relationships with many of the world’s most demanding institutional investors and corporations. For more information please visit www.cantor.com.
