Data Operations Engineer

Personify Health•Tempe, AZ

1d•$84,000 - $87,000•Onsite

About The Position

Data Operations Engineer supports the development and maintenance of data systems used in healthcare and TPA claims processing. This role assists with building and troubleshooting data pipelines, ensuring data accuracy across on-prem and cloud environments, and collaborating with senior engineers, analysts, and business teams. Approximately 50% of the role involves handling support tickets, including diagnosing pipeline issues, addressing data quality concerns, and responding to user requests. This position is ideal for someone early in their data engineering career with minimum 2 years of experience who is eager to learn and grow technical skills in ETL/ELT, SQL, and data workflows while contributing to operational and analytical needs across the organization.

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.
Some exposure to cloud environments (AWS, Azure, ) is preferred but not required.
Understanding of ETL/ELT pipelines, data validation, and data quality monitoring.
Experience handling support tickets or operational data issues is strongly preferred (~50% of role).
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.

Nice To Haves

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).

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.