Point72's Data Engineering Technology team provides a scalable data engineering capability and set of data services to support the firm's expanding data needs, focusing on solutions such as cloud computing, data platforms for large scale data processing, data governance, data quality, enterprise reference data, business automation, and high touch service.
Requirements
- Expertise in Databricks, including Spark (PySpark or Scala), Delta Lake, and notebook-based development workflows.
- Proficiency in building scalable, distributed data pipelines in a cloud environment (preferably Azure or AWS).
- Strong programming skills in Python and SQL.
- Solid understanding of data architecture principles, data modeling, and data warehousing.
- Experience with version control (e.g., Git), CI/CD workflows, and modern data orchestration tools (e.g., Airflow, dbt).
Responsibilities
- Design, develop, and maintain robust data pipelines and ETL workflows in Databricks to support quantitative research, trading, and risk management.
- Collaborate closely with data scientists, analysts, and portfolio managers to understand data needs and deliver scalable data infrastructure.
- Ingest, process, and normalize large volumes of structured and unstructured financial data from a variety of sources.
- Optimize performance of data pipelines and ensure high availability, reliability, and data quality across all production systems.
- Implement data governance best practices, including data lineage, cataloging, auditing, and access controls.
- Support the integration of third-party data vendors and APIs into the broader data ecosystem.
- Continuously evaluate and implement new tools and technologies to improve data engineering capabilities, with a focus on cloud-native and distributed processing frameworks.
Other
- 3–6 years of professional experience in data engineering or a similar role, ideally within a financial services or high-performance computing environment.
- Demonstrated ability to work collaboratively in a fast-paced, high-stakes environment with both technical and non-technical stakeholders.
- Commitment to the highest ethical standards
- Bachelor’s or master’s degree in computer science, engineering, or a related technical field.
- Fully paid health care benefits
