Data Quality Analyst (US-Remote)

You'll test incoming data and product outputs, spot problems before they reach customers, investigate what may be causing them, and clearly document issues for the product and engineering team to resolve. Part-time contract role averaging 15-20 hours/week for an initial 6-month term, with potential to convert to full-time based on performance, business needs, and mutual fit.

Company
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Job description

About Huckleberry Signals

Huckleberry Signals is an AI-powered data intelligence platform built for grower-packer-shippers in the fresh produce industry. Our customers are drowning in data and starving for answers. 

We help them turn scattered reports and spreadsheets into clear, trustworthy insight.

The Role

We're looking for a Data Quality Analyst to make sure the answers and numbers our customers see are right. This role sits close to the data every day. You'll test incoming data and product outputs, spot problems before they reach customers, investigate what may be causing them, and clearly document issues for the product and engineering team to resolve.

This is a part-time contract role with a small, fast-moving team. There won't be someone looking over your shoulder day to day, so this role requires someone who is genuinely independent and self-directed. If you need regular check-ins to stay on track, this isn't the right fit. If you can take a task, run with it, and flag problems on your own before they're asked about, that's exactly what we need.

**Please note:

• Part-time contract role averaging 15-20 hours/week for an initial 6-month term, with potential to convert to full-time based on performance, business needs, and mutual fit.
• Hours may occasionally increase to 25 hours/week; a few hours of overlap with US-Mountain or Central Time is preferred.
• Immediate need: candidates should be available to interview and onboard promptly if selected.

What You'll Do

• Review incoming customer data and product outputs for accuracy, completeness, and consistency
• Test Huckleberry's AI-powered product by asking questions and identifying missing, inconsistent, or unexpected answers
• Spot-check catalog entries and business logic against source documentation
• Catch anomalies and issues before they reach customers
• Investigate potential causes and provide clear details to the product and engineering team
• Document data quality issues, observations, and decisions so the team can quickly act on them
• Flag patterns that suggest a bigger process problem, not just a one-off error

What You'll Need

• A proven track record of working independently. This is a must, not a nice-to-have. You should be comfortable managing your own time and priorities without close supervision
• 2–3 years of experience in data quality, data analysis, QA, or a similar role
• Working knowledge of SQL. You should be comfortable reading and understanding queries, joins, filters, and aggregations well enough to investigate potential data issues
• Solid spreadsheet skills (Excel or Google Sheets)
• Strong attention to detail and an investigative mindset
• Good judgment. You know when a number or answer looks wrong and are willing to dig into why
• Clear, direct written communication
• Comfort asking questions when something doesn't add up instead of guessing

Nice to Have

• Experience working with AI or LLM-powered products
• Experience with a cloud data warehouse such as BigQuery
• Familiarity with dashboard tools such as Superset, Tableau, or Looker
• Background in agriculture, food supply chain, or produce industry data