Data Systems Engineer

Central Health • Austin, TX

2d

About The Position

The Central Health System Data Engineer designs, develops, and maintains scalable data systems that support enterprise reporting, analytics, data science, AI, and operational workflows. The role requires cloud-native data engineering expertise, including pipeline development, data modeling, and platform optimization in Central Health’s Snowflake and Azure environment. It is responsible for automating enterprise data import and export, maintaining data integrity across internal and external systems, and building reliable, well-documented data infrastructure.

The Data Engineer collaborates with Data Architects, Engineering leadership, internal and external enterprise partners, and the Data Integration team to establish and uphold data engineering and governance practices. The role contributes to the evolution of Central Health’s data capabilities, including analytics engineering and applied AI, and serves as a technical contributor across the Data Engineering and Integration Services team.

Requirements

• Bachelor’s degree in computer science or a related field; alternatively, an associate’s degree in computer science or a related field plus one additional year of related experience; or a high school diploma, equivalent, or GED plus two additional years of related experience.
• At least 1 year of experience in Healthcare IT.
• At least 2 years of experience in data engineering, database development, or a related role.
• At least 2 years of experience writing advanced T-SQL and/or Python for data processing, automation, or pipeline development.
• At least 2 years of experience with cloud data platforms such as Snowflake, Azure SQL, Azure Data Factory, or equivalent.
• At least 1 year of experience with data pipeline or ETL/ELT development and orchestration.
• Familiarity with data integration concepts and interoperability standards in a healthcare or enterprise environment.
• EPIC certification within 6 months.
• Boomi Professional Developer certification within 3 months.
• Snowflake SnowPro Core Certification within 3 months.
• Microsoft Certified: Azure Data Engineer Associate (DP-203) within 6 months.

Responsibilities

• Design, develop, test, and maintain scalable ELT/ETL pipelines using Azure Data Factory, dbt, Python, and Snowflake.
• Build and optimize Snowflake data models, including star/snowflake schemas and dimensional models, for analytics and operational reporting.
• Develop, test, and maintain Snowflake objects.
• Write advanced T-SQL and Python scripts for data transformation, automation, and data quality enforcement.
• Automate data extraction, transformation, and loading to reduce manual intervention and improve reliability.
• Investigate and troubleshoot coding errors and data flow failures.
• Participate in assessing and migrating SQL Server objects, including stored procedures and SSIS packages, to Snowflake and Azure-native equivalents where applicable.
• Validate migrated data for completeness, accuracy, and consistency against source systems.
• Document migration decisions, data lineage, and transformation logic throughout modernization.
• Ensure data accuracy, completeness, and consistency across pipelines and data products; investigate and resolve failures and anomalies.
• Analyze data quality issues and develop solutions to maintain platform integrity and efficiency.
• Coordinate with the Data Integration team on data transport, interface issues, and cross-system data flows as needed.
• Follow data governance standards and contribute to data cataloging and documentation, such as in OvalEdge.
• Coordinate with QA Specialists to develop and execute test plans that verify pipelines and systems meet design requirements.
• Collaborate with Data Architects, database administrators, and other Joint Technology team members.
• Partner with Data Engineering & Integration Services teammates and cross-functional stakeholders to deliver projects.
• Serve as a subject matter expert during project planning in collaboration with the Project Management Office.
• Answer provider, partner, and vendor questions and assist with troubleshooting and resolving data-related problems.
• Create and maintain schema documentation, data dictionaries, and other technical artifacts.
• Follow coding standards, participate in peer code reviews, and use standardized tools to document work and track progress.
• Perform vendor management and oversight as needed.
• Work outside standard business hours when required.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level