Data Quality Engineer

This role is part of a cross-functional team that includes team members from Engineering, Product, and Solutions to deliver on product launches and iterations. The Data Quality Engineer will own the integrity, validation, and reliability of the data pipelines that power the product, working directly with external data vendors to ensure the data feeding the product is accurate, timely, and fit for purpose.

What You Will Do

• Design and execute frameworks for data quality assurance and validation
• Collaborate across the organization to implement new features, support internal stakeholders, and investigate and improve data infrastructure.
• Partner with the Sr. Engineer, Quantitative Modeler, and Solutions Architect to ensure data feeding the product and financial models is validated and launch-ready
• Participate in stand-ups and other milestone meetings to maintain momentum and alignment across the team.
• Serve as the data quality checkpoint between vendor data ingestion and product delivery, catching issues before they surface downstream
• Establish data quality monitoring and documentation to support the pipeline post-launch
• Surface data quality risks and vendor issues to the Director of Engineering in time to inform launch decisions
• Manage external data vendor relationships and ensure ongoing data quality and validation

What You Will Need

• Python codingfor productionsystems (modular code, notjupyternotebooks)
• Git workflow and collaborative code review
• Docker images and container build tooling
• Data validation and verification pipeline design, including automated testing
• Data quality assessment and solution feasibility analysis
• Data exploration and engineering tools: pandas, SQL, and similar
• DAG-based ETL orchestration (Prefect or similar)
• AWS, especially S3

Jupiter’s Tech Stack

• Prefect workflow jobs and ETL
• Python (with heavy use of Pydantic and pytest)
• Snowflake and Postgresql SQL
• Temporal durable execution engine

What Sets You Apart

• 3+ years of experience in data engineering, data quality, or analytics engineering roles
• Bachelor’s degree in computer science, statistics, or a related field. Equivalent practical experience also considered.
• Experience managing or coordinating with external data vendors, including data quality troubleshooting
• Experience working in a fast-paced, cross-functional environment, ideally supporting a product launch or similar high-stakes delivery
• Experience partnering with quantitative or financial roles (e.g., financial modeling, data science) or experience in climate tech strongly considered.