Data Quality Engineer – Contractor

Job not on LinkedIn

🕒 September 21

🏄 California, Colorado, +1 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🗽 New York – Remote

💵 $55 - $65 / hour

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 3%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Jupiter Intelligence

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

💼 Consulting

📦 Logistics

🤖 Artificial Intelligence

Consulting • Logistics • Artificial Intelligence

Jupiter Intelligence is a leader in providing decision-ready climate risk analytics to help organizations understand and manage their exposure to physical climate risks. Utilizing advanced methodologies and artificial intelligence, Jupiter delivers comprehensive data solutions that enable businesses to navigate climate risk regulations, enhance resilience, and report on climate impacts effectively. Their services cater to various sectors, including banking, insurance, and energy, offering insights that are essential for compliance and operational risk management in a changing climate.

📋 Description

• 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

• 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

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

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