L2 Production Support Engineer (Healthcare Data Production Support Engineer)
Why This Role Stands Out
Leverage your expertise in SQL, ETL, and Python automation to directly impact critical healthcare data pipelines in this fully remote L2 Production Support Engineer role. You'll thrive in this position if you possess strong analytical skills and enjoy troubleshooting complex data challenges within a dynamic environment. Apply now to join a reputable company and grow your career in the vital healthcare technology sector.
Quick Overview
Job Description
Job Summary
We are looking for an experienced Data/ETL Production Support Engineer with strong SQL and ETL experience and hands-on exposure to Python automation.
The candidate will support healthcare data pipelines, file processing, database tables, and ETL workflows. The role involves monitoring incoming files, validating data loads, performing source-to-target reconciliation, troubleshooting data discrepancies, and automating repetitive validation activities using Python.
The ideal candidate should be comfortable working with a high volume of files and tables and should have experience supporting production data processes in a healthcare environment.
- Provide production support for healthcare data and ETL processes.
- Monitor scheduled file arrivals and ETL jobs.
- Validate database tables after ETL processing.
- Perform source-to-target data validation and reconciliation.
- Support onboarding of new files and database tables.
- Validate new tables against source files and ETL mappings.
- Investigate ETL failures and data discrepancies.
- Identify root causes and coordinate with Data Engineering/Development teams for resolution.
- Develop Python scripts to automate repetitive file and database validation activities.
- Improve existing manual validation processes through automation.
- Monitor production jobs and provide timely issue resolution.
- Maintain validation procedures, support documentation, and operational runbooks.
- Work with business and technical teams to understand healthcare data requirements.
- Follow healthcare data security and compliance requirements when handling sensitive data.
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