The Data Engineer will play a critical role in architecting and developing robust data pipelines that process millions of healthcare claims daily. You will work closely with engineers, product managers, and business stakeholders to build the data infrastructure that drives payment accuracy and business intelligence across Rialtic's platform.
What You Will Do
• Develop clear, observable, and well-tested data pipelines in Python
• Build automation to enable effective integration testing and deployment
• Streamline transformations across multiple data formats and sources
• Interface data pipeline strategies with core architecture including Kafka, data lakes, and reporting tools
• Contribute to data warehouse and lake architecture decisions
• Collaborate with internal stakeholders to drive data-driven business value
What You Bring
• 3–6 years of hands-on software development experience
• 3+ years building and evolving data pipelines and data warehouses or lakes
• 3+ years with Python, PySpark, Pandas, and related data processing frameworks
• 2+ years with compiled languages such as Go, C#, or C
• 2+ years with job orchestration tools such as Airflow, Mage, or AWS Step Functions
• 2+ years working with SQL and NoSQL databases
• Exposure to queuing and pipeline technologies such as Kafka or SQS
• Familiarity with data testing tools such as Great Expectations
Nice to Have
• Experience in healthcare or claims data environments
• Familiarity with Spark connectors and distributed data processing
Tech Stack
Python, PySpark, Airflow, Kafka, Athena, Postgres, AWS, Kubernetes