Data Platform Engineer

This role focuses on building the foundation that supports data science, quantitative research, and investment workflows. You will design and maintain the systems that turn raw data into usable insights. The work sits at the center of how teams access, analyze, and act on data, and you will partner closely with researchers, engineers, and product leads to make that possible.

This is an in-office role with a consistent on-site schedule.

What You’ll Do

• Build and maintain reliable data pipelines that support research and investment use cases
• Own and improve the underlying data platform used by a wide range of internal teams
• Work with domain experts to transform specialized datasets into practical insights
• Ship tools and features that make it easier for others to work with data
• Collaborate with data scientists to design schemas, pipelines, and scalable data models
• Partner with product managers to shape and expand internal data systems
• Work across a modern stack that includes Python, SQL, distributed processing tools, and workflow orchestration systems

What You Bring

• 3 to 7 years of experience in data engineering, with a track record of delivering complete projects
• Strong skills in Python and SQL, with experience in distributed processing frameworks as a plus
• Experience building and deploying data ingestion pipelines that integrate multiple external sources
• Familiarity with relational databases such as PostgreSQL or similar systems
• Comfort working with both structured and unstructured data
• Clear communication skills and the ability to work closely with technical and non-technical partners

Nice to Have

• Experience working with cloud infrastructure such as object storage or file transfer systems
• Familiarity with APIs or messaging systems
• Exposure to containerization or distributed computing frameworks
• Experience building data systems from scratch
• Background in finance, quantitative research, or data-heavy environments