Happiest Minds
Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes to transform diverse healthcare data into the Verana common data model. Conduct deep-dive initial analysis and data profiling on newly integrated EHR and Practice Management (PM) systems to understand their underlying schemas. Investigate and reverse-engineer clinical workflows to understand exactly how data is captured at the point of care across 3,000+ clinical practices. Identify, trace, and resolve complex data quality anomalies caused by custom clinic configurations and variations across 20+ different EHR vendors. Develop highly efficient, advanced SQL queries and Python scripts to perform complex data transformations and normalization. Apply and map standard healthcare coding terminologies including CPT, ICD, SNOMED, NDC, and LOINC to ensure comprehensive data standardization. Leverage industry data frameworks like HL7 FHIR to guide and optimize target common data model (CDM) mapping strategies. Collaborate with cross-functional teams, external EHR vendors, and practice IT administrators to isolate and resolve upstream workflow or data ingestion issues. Mandatory Skills Expert-level SQL skills for data profiling, complex joins, window functions, and deep-dive data forensics. Strong hands-on experience with ETL/ELT concepts, data transformation, and source-to-target schema mapping. Working experience with Python for data engineering, automation, and script writing. Deep domain experience in healthcare data, specifically analyzing and manipulating native EHR and Practice Management (PM) data structures. Strong mastery of clinical coding systems and healthcare terminologies, including CPT, ICD-9/10, SNOMED-CT, NDC, and LOINC. Experience with relational data modeling, schema design, and mapping disparate sources into a unified Common Data Model (CDM). Proven track record in managing data quality, integrity, and data profiling to catch anomalies before they reach production. Strong problem-solving skills with a "data detective" mindset to unearth hidden data and reverse-engineer structural workflow variations. Excellent technical communication skills with the ability to translate complex data discrepancies to non-technical stakeholders and external clinical partners. Desired Skills Conceptual or working familiarity with HL7 FHIR standards and specification frameworks. Experience working with large-scale distributed datasets and modern cloud data warehouses (e.g., AWS Snowflake, Redshift, Databricks). Familiarity with clinical data registries, healthcare informatics, or life sciences data analysis.