Data Quality Engineer – Contractor

Jupiter Intelligence

. Design and execute frameworks for data quality assurance and validation .

Posted 9/21/2026contractRemote • United StatesMid-LevelSenior💰 $55 - $65 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data quality assurance, validation, and engineering, with a strong focus on Python coding, data pipeline integrity, and collaboration with cross-functional teams. Proficient in managing external data vendor relationships and ensuring high standards of data quality and reliability.

Highest-signal resume keywords

Python Coding for Production SystemsData Validation and Verification Pipeline DesignDAG-Based ETL OrchestrationAWS, Especially S3Data Quality Assessment and Solution Feasibility Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Quality AssuranceData ValidationData EngineeringData ExplorationAutomated TestingSQLPandasDockerGit WorkflowData Quality Troubleshooting

Soft Skills

CollaborationCross-Functional CommunicationProblem-SolvingStakeholder Management

Tools & Technologies

Docker ImagesContainer Build ToolingPrefectData Pipeline MonitoringData Documentation

Industry Keywords

Data QualityAnalytics EngineeringClimate TechFinancial ModelsVendor Management

Tech Stack

Tools & technologies

AWSDockerETLPandasPythonSQL

About the role

Key responsibilities & impact

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 milestone meetings
Serve as the data quality checkpoint between vendor data ingestion and product delivery
Establish data quality monitoring and documentation to support the pipeline post-launch
Surface data quality risks and vendor issues to the Director of Engineering
Manage external data vendor relationships and ensure ongoing data quality and validation
Own the integrity, validation, and reliability of product data pipelines

Requirements

What you’ll need

Python coding for production systems (modular code, not Jupyter notebooks)
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
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 or experience in climate tech strongly considered
Must be authorized to work in the US

Benefits

Comp & perks

Equal opportunity and inclusive work environment
Base pay transparency
Compensation adjusted for part-time hours