We are looking for a highly skilled Product Engineer to design and optimize scalable data pipelines and develop robust data products. This role focuses on leveraging technologies like Databricks, PySpark, and SQL to build high-performance, production-grade data workflows. You'll collaborate with cross-functional teams including data scientists and quant teams to support data-driven decision-making across structured, unstructured, and alternative data sources.
Key Responsibilities:

• Design, build, and optimize scalable data pipelines.
• Develop and operationalize data products across structured and unstructured data, including alternative data sources.
• Deploy, manage, and tune Spark workloads on Databricks, ensuring scalability and cost-efficiency.
• Collaborate with data science and business teams to deliver data-driven insights.
• Support CI/CD automation, infrastructure-as-code, and reusable data frameworks.

Essential Skills:

• Strong experience with Python and PySpark.
• Hands-on expertise with Databricks components: Jobs, Workflows, Delta Lake, Unity Catalog.
• Proficiency in SQL for advanced data transformations.
• Deep understanding of distributed data processing and production-grade data workflows.

Desirable Skills:

• Exposure to Machine Learning tools like MLflow.
• Experience with alternative data (web, geospatial, satellite, sentiment).
• Familiarity with Snowflake, Airflow, or other orchestration/warehousing platforms.
• Understanding of CI/CD, version control, and deployment best practices.