Posted August 22, 2026
Data Engineer
Robert Half
Dallas, TX, US
Full Time
60USD - 70USD per hour
Job Description
Job Description
We are looking for a Data Engineer to join a mission-driven team, where you will design and support the data foundation behind clinical reporting, advanced analytics, and predictive healthcare solutions. This contract position offers the opportunity to build dependable, scalable data workflows that deliver information from healthcare platforms and other source systems to clinicians and business teams. The role is highly hands-on and centers on transforming complex healthcare data into trusted, well-structured assets that support operational and clinical decision-making.
Responsibilities:
• Design, develop, and maintain robust data pipelines that move information from healthcare platforms and related source systems into analytics and reporting environments.
• Prepare, standardize, and validate data from claims, clinical records, and social determinants of health sources to ensure accuracy and usability.
• Apply sound data modeling practices to organize information for warehousing, business intelligence, and advanced analytical use cases.
• Build scalable processing solutions using tools such as Python, Apache Spark, Hadoop, and Kafka to support high-volume data operations.
• Partner with analytics, clinical, and business stakeholders to deliver reliable datasets that power descriptive, predictive, and prescriptive insights.
• Monitor pipeline performance, troubleshoot data issues, and improve the reliability and efficiency of end-to-end ETL processes.
• Support the full lifecycle of data initiatives, from source integration and transformation through delivery for reporting and analytical applications.• Extensive experience in data engineering, with a strong focus on building and supporting enterprise data pipelines.
• Hands-on proficiency with Python for data processing, automation, and pipeline development.
• Experience working with Apache Spark and Hadoop in large-scale data environments.
• Familiarity with Apache Kafka or similar streaming technologies for data movement and integration.
• Strong understanding of ETL development, including extraction, transformation, validation, and loading of complex datasets.
• Knowledge of data warehousing concepts and data modeling best practices.
• Ability to work with healthcare-related data such as claims, clinical, or social determinants of health information.
• Comfortable collaborating in a fast-paced environment where data solutions support operational and clinical outcomes.
Responsibilities:
• Design, develop, and maintain robust data pipelines that move information from healthcare platforms and related source systems into analytics and reporting environments.
• Prepare, standardize, and validate data from claims, clinical records, and social determinants of health sources to ensure accuracy and usability.
• Apply sound data modeling practices to organize information for warehousing, business intelligence, and advanced analytical use cases.
• Build scalable processing solutions using tools such as Python, Apache Spark, Hadoop, and Kafka to support high-volume data operations.
• Partner with analytics, clinical, and business stakeholders to deliver reliable datasets that power descriptive, predictive, and prescriptive insights.
• Monitor pipeline performance, troubleshoot data issues, and improve the reliability and efficiency of end-to-end ETL processes.
• Support the full lifecycle of data initiatives, from source integration and transformation through delivery for reporting and analytical applications.• Extensive experience in data engineering, with a strong focus on building and supporting enterprise data pipelines.
• Hands-on proficiency with Python for data processing, automation, and pipeline development.
• Experience working with Apache Spark and Hadoop in large-scale data environments.
• Familiarity with Apache Kafka or similar streaming technologies for data movement and integration.
• Strong understanding of ETL development, including extraction, transformation, validation, and loading of complex datasets.
• Knowledge of data warehousing concepts and data modeling best practices.
• Ability to work with healthcare-related data such as claims, clinical, or social determinants of health information.
• Comfortable collaborating in a fast-paced environment where data solutions support operational and clinical outcomes.
