Healthcare Data Engineer, Team Lead

Apply Job Type Full-time Description About Hart Hart is a leader in healthcare data accessibility and infrastructure, delivering intelligent solutions that empower health systems to manage, move, and protect their clinical and financial data. Founded in 2012 in Orange County, California, Hart serves hospitals and health networks across the U.S., helping them simplify EHR data migrations, archival, interoperability, and analytics through its suite of innovative products and professional services. Hart’s mission is to make healthcare data accessible, secure, and actionable—so providers can focus on what truly matters: improving patient outcomes. Our growing portfolio includes HealthMigrate, HealthArchive, HealthExchange, HealthLake, HealthSecure, and HealthSync—each designed to address a specific challenge in modern healthcare data management. Job Summary Hart is seeking a motivated, healthcare data engineer with minimum 5 years of experience to join our Delivery team as a technical team lead. This role focuses on developing, maintaining, and improving ETL processes that support EHR migration, archival, and interoperability solutions. As Implementation Technical Lead, you will provide day-to-day technical leadership, documentation, guidance, and support for Hart’s Implementation Engineering function. You will be responsible for improving the consistency, quality, scalability, and efficiency of technical client implementations while strengthening collaboration between Implementation Engineering, Platform Engineering, Project Management, and other Delivery functions. The ideal candidate has hands-on experience in healthcare data engineering and is eager to expand their expertise in cloud, security, and compliance frameworks. Key Responsibilities ETL Development: Design, build, and optimize SQL, Python, and Scala-based data transformation tools to support EHR migrations, data archiving, and data streaming initiatives. Data Integration: Develop and maintain scalable processes for ingesting and normalizing structured and unstructured healthcare data from multiple sources (e.g., EHRs, HL7, FHIR) Data Quality & Validation: Implement data quality checks and validation rules to ensure accuracy, completeness, and consistency across systems. Automation & Optimization: Identify opportunities to automate ETL workflows, improve performance, and enhance system reliability. Collaboration: Work closely with project managers, analysts, and solution architects within the Delivery team to translate client data requirements into technical solutions. Documentation: Maintain thorough documentation for data mappings, transformation logic, and system configurations. Security & Compliance: Adhere to Hart’s data protection standards and ensure compliance with HIPAA, SOC 2, GDPR, and HITRUST frameworks. Support & Troubleshooting: Diagnose and resolve data-related issues, ensuring minimal disruption to client projects Requirements Qualifications: - Bachelor's degree in computer science, information systems, or a related field. Relevant certifications and additional education are a plus. - Strong experience (5+ years) as a Data Engineer or similar role, with a focus on data transformation and ETL development. - Solid understanding of data transformation concepts, data modeling, and database design principles. - Expertise in SQL programming, including complex query development, stored procedures, and database performance optimization with proficiency in working with relational databases (e.g., Oracle, SQL Server, MySQL) and related tools. - Strong experience (5+ years) with object oriented languages including SQL, Python, or Scala - Experience with distributed data/computing tools (Hadoop, Spark) and cloud-based data services (AWS) - Familiarity with healthcare data standards (e.g., HL7, FHIR) and healthcare-related regulatory requirements (e.g., HIPAA) is highly desirable. - Strong analytical and problem-solving skills, with the ability to identify data-related issues and implement effective solutions. - Detail-oriented mindset with a focus on data accuracy, quality, and integrity. - Excellent communication and collaboration skills to effectively work with cross-functional teams and stakeholders. - Ability to work in a fast-paced, dynamic environment and manage multiple priorities. - Proven ability to work independently and with a team.