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Do you have a solid knowledge of SQL and been around the healthcare data biz for a bit? If so, read on…
Open Professional Group, a dynamic software development company, is seeking the right individual that knows how to work with data, and has some experience in healthcare data sets. We don’t need a data scientist, we need someone that can review, understand, parse and run calculations on large blocks of healthcare data.
You’re the first line of defense in a high-volume healthcare data environment — the kind of person who gets genuine satisfaction from turning chaos into clean, validated data. If spotting a missing delimiter or diagnosing a weird row count gives you a quiet thrill, we want to talk to you.
You’ll be at the center of our intake process, monitoring hundreds of inbound files each month, performing pre-checks and validations, and making sure everything flows smoothly downstream to our ETL and QA teams. You’ll use SQL, spreadsheets, and a bit of Python to keep things humming — and clear communication to keep everyone aligned.
** If you are a self taught data junkie, you are encouraged to apply if you have experience. Actual work with data is the best teacher!
What You’ll Do
- Keep the data gates: Watch SFTP and API drop points; confirm file arrivals match the manifest and log them accurately.
- Run smart pre-checks: Build data maps, validate layouts, encodings, headers, and key fields before data ever hits production.
- Hunt down anomalies: Write quick SQL queries to uncover duplicates, missing keys, or overlap issues.
- Raise (and resolve) flags: Log exceptions, escalate critical issues fast, and document what went wrong (and how you fixed it).
- Report with clarity: Generate clean, simple summaries to communicate findings to both techies and business stakeholders.
- Collaborate and improve: Work hand-in-hand with Intake, QA, and ETL teammates to tighten validation rules and reduce recurring issues.
- Document your brilliance: Keep runbooks and SOPs fresh to ensure that the process stays current.
Your Typical Day
- Start your morning by checking file manifests and verifying inbound data.
- Run validation scripts and SQL checks to spot any “gotchas.”
- Update the daily tickets with what’s ready, what’s missing, and what needs attention.
- Troubleshoot data anomalies (bonus points for discovering a pattern before it becomes a problem).
- Maintain effective notes and documentation to keep the whole team running efficiently
What You Bring
- SQL fluency (MySQL 8): comfortable with joins, filters, data typing, groupings, and understanding query performance.
- File wrangling skills: you understand CSVs, delimiters, encodings, and how to spot structural mismatches.
- Linux comfort: navigating directories, verifying file arrivals, checking logs — you know your way around a terminal.
- Attention to detail: meticulous record-keeping and consistent process discipline are your superpowers.
- Clear communication: you can explain a data issue to a developer or a project manager without losing either one.
- Spreadsheet mastery: reviewing data and finding patterns quickly and easily once extracted from the data warehouse
Nice to Have
- Python (especially Pandas or Jupyter) for lightweight automation and analysis.
- Familiarity with SFTP tools and data automation pipelines.
- Exposure to healthcare data (enrollment, claims, Rx) and understanding of identifiers like subscriber or dependent IDs.
- Experience using ticketing/documentation tools (Teamwork, Jira, Confluence, etc.).
Why You’ll Love It Here
- Work in a collaborative, learning-driven environment that values curiosity as much as accuracy.
- Be part of a team that actually documents what it does — and rewards ideas that improve the process.
- Enjoy flexible hours and a remote-first culture with clear expectations and strong communication.
- See the impact of your work every day as clean, validated data powers real decisions in healthcare operations.
Job Type: Full-time
Job Type: Full-time
Pay: $70,000.00 – $90,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Paid time off
Experience:
- SQL: 1 year (Required)
- Relational database: 3 years (Preferred)
- Data analysis: 1 year (Preferred)
- Healthcare data: 1 year (Preferred)
Work Location: Remote
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