Soros Fund Management LLC (SFM) is seeking an experienced Data Engineer to build and refine robust data systems, including developing efficient data pipelines for trading and risk management, and modernizing legacy systems with cloud-based tools like Snowflake and DBT.
Requirements
- 6+ years of development experience with 2+ years focused on data engineering.
- Excellent Python and SQL skills for data processing and automation.
- Extensive ETL/ELT pipeline experience and expertise.
- Strong understanding of data structures, data modeling, efficient query design and performance tuning in a SQL database such as Postgres or MS SQL Server.
- Familiarity with data transformation tools such as DBT.
- Experience building and deploying containerized applications (Docker, Kubernetes) in cloud environments.
- Hands-on experience with Snowflake, Databricks, or similar.
Responsibilities
- Design, develop and optimize data pipelines for trading, alpha generation, research, risk management, accounting, and more.
- Build new golden source datasets such as security master, account master, and price master which are critical to the firm.
- Develop shared Python libraries for data APIs, logging, and other core functionalities.
- Expand and tune our AI offering for LLM search & summarization of financial documents and market commentary.
- Ensure high data quality and observability using modern data governance tools.
- Optimize large-scale data processing workflows for efficiency and performance.
- Support and troubleshoot data pipelines, APIs, and database performance issues.
Other
- Great communication and capable of cross-functional collaboration.
- Excellent problem-solving skills.
- Financial market data literacy with product knowledge spanning equities, fixed income, futures, and options.
- Experience designing dashboards in a Business Intelligence tool.
- Smart risk-taking // Owner’s Mindset // Teamwork // Humility // Integrity
