Data Operations Engineer

Personify Health is hiring a Data Operations Engineer to support the development and maintenance of data systems used in healthcare and TPA claims processing. The role maintains and troubleshoots data pipelines, monitors data accuracy and system processes, handles operational support tickets, and collaborates with technical and business teams.

Responsibilities:

• Assist in maintaining and troubleshooting ETL/ELT data pipelines used for healthcare and TPA claims processing
• Work with Python and SQL to support data extraction, transformation, validation, and loading across on-prem and cloud environments
• Help monitor pipeline performance and resolve data issues, including reviewing logs, investigating failed jobs, and correcting data discrepancies
• Handle support tickets (~50% of the time), responding to user requests, researching data questions, and helping resolve operational data problems
• Supports daily process monitoring, including checking production processes and/or jobs, application performance, application maintenance, etc
• Support data management tasks in systems such as PostgreSQL, Oracle, and cloud-based databases
• Work with senior team members to learn data workflows, healthcare data formats, file transfers, and reporting processes
• Assist in maintaining data quality and accuracy through routine checks, documentation, and follow-up
• Collaborate with Data Analysts, Developers, and business users to understand data needs and support ongoing reporting and data operations
• Participate in team meetings, sprint activities, and knowledge-sharing to continue developing data engineering skills

Requirements:

• AWS Certification (or willingness to obtain within 6–12 months), such as AWS Cloud Practitioner or AWS Developer – Associate
• 2–3 years of experience in data engineering, analytics engineering, or a related technical role
• Proficiency in Python and SQL, including writing queries, joins, basic transformations, and troubleshooting
• Hands-on experience with relational databases (PostgreSQL, Oracle, AWS RDS) and familiarity with basic data warehouse concepts
• Understanding of ETL/ELT pipelines, data validation, and data quality monitoring
• Basic knowledge of Linux command line for navigating servers and running scripts
• Familiarity with collaboration tools such as JIRA and Git/Bitbucket
• Strong attention to detail and focus on data accuracy and reliability
• Effective written and verbal communication skills; able to document findings and processes
• Demonstrated ability to manage time, prioritize tasks, and follow through on commitments
• Collaborative mindset, able to work with both technical and non-technical team members
• Self-motivated, able to prioritize tasks, and eager to learn from senior team members
• Interest in developing skills in ETL workflows, data pipelines, and cloud data environments over time
• Some exposure to cloud environments (AWS, Azure, ) is preferred but not required
• Experience handling support tickets or operational data issues is strongly preferred (~50% of role)
• Experience with healthcare EDI formats (e.g., 834, 835, 837, 999)
• Exposure to AWS services (e.g., S3, RDS, Lambda) or cloud-based data tools
• Experience with orchestration tools (Airflow), containers (Docker), or CI/CD pipelines
• Familiarity with relational databases such as PostgreSQL, Oracle, or AWS RDS
• Familiarity with AWS services (S3, RDS, Lambda, Glue) or modern data warehouses (Redshift, Snowflake)
• Basic understanding of data modeling concepts (star/snowflake schemas, dimensional modeling)