Data Engineer

About This Position

Waystar, the leading Healthcare Revenue Cycle Management (RCM) technology company, is seeking a skilled Data Engineer to support our growing Data Licensing and Resale product team. In this role, you will design, build, and optimize scalable data pipelines and infrastructure to support the delivery of licensed data products and insights to customers. You will work with complex healthcare data from multiple source systems and ensure data accuracy, reliability, and performance using modern cloud platforms like Snowflake and Google Big Query, along with SQL, Python, SQL Server, and Postgres.

The ideal candidate will have an understanding of healthcare data and RCM processes, with strong technical expertise and the ability to collaborate across data, product, and business teams to build data products that deliver high-quality, accurate insights to clients. You will play a key role in building the infrastructure needed to support data monetization strategies and ensuring that licensed data products meet customer expectations for performance and accuracy.

• Data Architecture and Engineering
• Design and implement scalable, high-performance data pipelines using Snowflake and Google Big Query to deliver licensed data products to customers.
• Develop and maintain ETL/ELT processes to ingest, transform, and store structured and unstructured data, ensuring data accuracy and timeliness.
• Build data infrastructure to support real-time and batch processing use cases for customer-facing products.
• Establish and enforce data quality and privacy standards and monitoring to ensure consistent and accurate data delivery to customers.
• Monitor and troubleshoot data pipeline performance issues and implement proactive improvements to minimize downtime and data delivery delays.
• Data Modeling and Integration
• Design and implement data models to support data licensing and resale use cases, ensuring they meet customer requirements and business goals.
• Integrate data from multiple source systems, including SQL Server, Postgres, and external APIs, ensuring data consistency and reliability.
• Create and maintain data dictionaries and metadata to support customer understanding and self-service analytics.
• Implement data partitioning, indexing, and clustering strategies to improve query performance and reduce processing time.
• Develop and maintain secure de-identification and data-sharing mechanisms to ensure appropriate access controls for licensed data products.
• Data Licensing and Product Support
• Work closely with product and business teams to define data product requirements and deliver licensed data products that meet customer expectations.
• Implement secure data-sharing protocols to ensure that licensed data is accurately and efficiently delivered to customers.
• Design and implement data anonymization and de-identification processes to meet data privacy and HIPAA compliance requirements.
• Create scalable data delivery mechanisms to support on-demand and scheduled data access for external clients.
• Ensure data licensing agreements and customer contracts are reflected accurately in data access controls and delivery processes.
• Value Delivery and Customer Outcome Achievement
• Partner with business and product teams to understand customer goals and translate them into data engineering solutions.
• Ensure that data products and pipelines deliver measurable business value and directly improve customer outcomes (e.g., better claim processing insights, faster payment reconciliation).
• Establish KPIs to track the business impact of data solutions and continuously improve them.
• Actively identify opportunities to improve data quality and speed of delivery to enhance customer experience and support data product growth.
• Automation and Performance Optimization
• Automate repetitive data processing tasks using Python and SQL to reduce manual effort and increase efficiency.
• Monitor and optimize data pipeline performance, addressing bottlenecks and failures to improve customer satisfaction.
• Leverage Snowflake’s performance features (e.g., micro-partitions, clustering, materialized views) to optimize query performance.
• Implement data orchestration using…