Senior Data Engineer (Healthcare Data)

Salt Square is a growing outsourcing company providing high-quality software development services to clients across a wide range of industries. Our team is composed of skilled and dedicated professionals delivering innovative solutions that meet and exceed client expectations. Our mission is to build reliable, scalable, and future-ready digital solutions tailored to each client’s unique business needs. We foster a team-first culture where collaboration, continuous learning, and technical excellence are core values. From supporting startups in launching their first products to helping global enterprises scale their operations, we strive to deliver outstanding value on every project. As a Data Engineer at Salt Square, you will build and maintain scalable healthcare data pipelines, transform legacy claims and clinical data into the FHIR® (Fast Healthcare Interoperability Resources) standard, and support population health analytics and regulatory compliance for payers and providers. We are looking for an experienced Senior Data Engineer to design, implement, and optimize scalable data solutions. You will work with modern data technologies, distributed systems, and cloud platforms to build efficient, high-performance data pipelines that support analytics, AI/ML, and business intelligence initiatives. Typical Responsibilities - Design, develop, and implement robust ETL/ELT pipelines for large-scale data ingestion, transformation, and storage. - Ensure data quality, integrity, and governance through validation techniques, data monitoring, and automated testing. - Work with data scientists, analysts, platform engineers, and business stakeholders to develop scalable, reusable data solutions. - Automate deployments and testing using CI/CD pipelines with Git, Terraform, GitHub Actions, or Jenkins. - Design and build custom data tools and abstractions for analytics, machine learning, and real-time data processing. - Partner with DevOps and platform teams to set up efficient deployment and monitoring processes for internal and external data products. - Develop alerting, monitoring, and observability frameworks that keep pipelines reliable and catch issues early. - Contribute to data architecture and strategy, improving scalability, performance, and cost efficiency. - Keep up with emerging technologies and best practices to continuously improve data engineering capabilities.