Data Quality Engineer: Reliable Data Pipelines

Jupiter Intelligence, Inc.; United States; On-site; USD 95,000 - 135,000; Part time

Job summary

Jupiter Intelligence, Inc. is seeking a Data Quality Engineer contractor to own data integrity, validation, and reliability across data pipelines. You will collaborate with Engineering, Product, and Solutions to ensure data from external vendors is accurate, timely, and fit for purpose.

The role requires Python, AWS, and ETL expertise, with a focus on data validation, testing, and monitoring to support launch-ready products.

Qualifications

• 3+ years of experience in data engineering, data quality, or analytics engineering roles.
• Bachelor's degree in computer science, statistics, or a related field, or equivalent practical experience.
• Experience coordinating with external data vendors and troubleshooting quality issues.
• Experience in fast-paced, cross-functional environments, supporting launches.
• Climate tech experience is strongly considered.

Responsibilities

• Design and implement data quality assurance and validation frameworks.
• Collaborate across teams to add features and support internal stakeholders.
• Ensure data feeding products and models are validated and launch-ready.
• Participate in stand-ups to maintain momentum and alignment.
• Serve as the data quality checkpoint between vendor ingestion and delivery.
• Establish data quality monitoring and post-launch documentation.
• Elevate data quality risks and vendor issues to engineering leadership.

Skills

Python production code

Git workflow

Docker

Data validation

Pandas/SQL

ETL orchestration

Prefect

AWS S3

Pydantic/pytest

Snowflake

PostgreSQL

Temporal engine

Education

Bachelor's degree in computer science, statistics, or related field

Tools

AWS

Prefect

Snowflake

PostgreSQL

Job description

Jupiter Intelligence, Inc. is seeking a Data Quality Engineer contractor to own data integrity, validation, and reliability across data pipelines. You will collaborate with Engineering, Product, and Solutions to ensure data from external vendors is accurate, timely, and fit for purpose.

The role requires Python, AWS, and ETL expertise, with a focus on data validation, testing, and monitoring to support launch-ready products.