Data Engineer (Healthcare ETL / HL7 / Data Migration)

Clearsense is seeking a hands-on Data Engineer to build healthcare data pipelines, reporting solutions, and migration processes. The role focuses on extracting, transforming, validating, and delivering healthcare data from EHR/EMR platforms and legacy systems while supporting data quality, archival, and modernization initiatives.

Responsibilities:

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, and AWS technologies
• Extract, transform, and load clinical, patient, financial, and operational healthcare data from EHR/EMR platforms, legacy databases, flat files, and APIs
• Support historical data migrations, conversions, archival projects, and large-scale data backfills
• Perform source-to-target mapping, data transformation, cleansing, and reconciliation
• Build reliable, reusable data processing solutions supporting multiple healthcare implementations
• Develop Python scripts and applications for data extraction, transformation, automation, and pipeline orchestration
• Write and optimize complex SQL queries, stored procedures, and data transformation logic
• Build and maintain data processing workflows using AWS services such as S3, Glue, Lambda, Athena, or Redshift
• Analyze large datasets, optimize pipeline performance, and troubleshoot complex data processing issues
• Develop scalable, maintainable solutions for healthcare data ingestion, transformation, and delivery
• Design, develop, and maintain SSRS reports, Power BI solutions, or comparable enterprise reporting tools
• Develop reporting datasets, SQL-based reporting logic, and data warehouse solutions
• Support clinical, financial, operational, and historical healthcare reporting requirements
• Perform comprehensive data validation, reconciliation, and quality assurance throughout migration and reporting projects
• Investigate discrepancies, validate data completeness, and ensure consistency between source and target systems
• Document reporting logic, data mappings, reconciliation results, and validation procedures
• Work directly with clinical and operational data from EHR/EMR platforms such as Epic, Oracle Health/Cerner, MEDITECH, Allscripts, NextGen, or similar systems
• Understand and interpret patient-level healthcare data, including encounters, diagnoses, medications, procedures, laboratory results, and related clinical records
• Work with healthcare interoperability standards such as HL7, FHIR, or C-CDA
• Maintain data integrity, privacy, and HIPAA compliance throughout data processing and migration activities
• Leverage AI-assisted development tools to support coding, debugging, documentation, testing, and engineering productivity
• Explore opportunities to apply AI to data processing, validation, automation, and workflow improvements
• Collaborate with Product, QA, Integration Engineering, and Client Delivery teams to deliver accurate and reliable healthcare data solutions
• Independently troubleshoot technical challenges and contribute to continuous process improvements

Requirements:

• 3–5+ years of professional experience in data engineering, ETL development, database development, or related technical roles
• Hands-on experience working with healthcare data, including clinical, patient-level, EHR/EMR, or hospital data
• Strong Python development skills, including ETL pipelines, data processing, scripting, and automation
• Advanced SQL skills, including complex queries, joins, stored procedures, transformations, and performance optimization
• Practical AWS experience, using cloud services for data ingestion, transformation, storage, or analytics
• Strong reporting experience, including SSRS, Power BI, Crystal Reports, or comparable reporting technologies
• Experience with ETL/ELT development, healthcare data migration, historical conversions, or legacy system modernization
• Experience with source-to-target mapping, data validation, reconciliation, and data quality assurance
• Experience working with healthcare interoperability standards such as HL7, FHIR, or C-CDA
• Practical experience using AI-assisted engineering tools or AI-enabled workflows to improve development, automation, or problem-solving
• Strong analytical, troubleshooting, communication, and technical documentation skills
• Experience with specific EHR/EMR platforms, including Epic, Oracle Health/Cerner, MEDITECH, Allscripts, or NextGen
• Experience with AWS Glue, S3, Lambda, Redshift, Athena, or similar cloud services
• Experience with SSIS, T-SQL, SQL Server, PySpark, Databricks, Snowflake, or Airflow
• Experience building AI-powered data pipelines, automated data quality checks, or intelligent mapping solutions
• Experience with large-scale clinical data migrations, historical backfills, and healthcare data archival platforms