ClinDCast is seeking a skilled ETL (Extract, Transform, Load) Developer with expertise in Tableau, Informatica, and a strong background in the healthcare domain. The ideal candidate will have a proven track record of designing, developing, and implementing ETL processes to extract, transform, and load data from various sources into data warehouses and reporting systems. This role requires a deep understanding of both technical ETL processes and the healthcare industry to ensure accurate and efficient data integration. Responsibilities: Data Extraction, Transformation, and Loading: Design, develop, and implement ETL processes to extract data from diverse sources, transform it into a suitable format, and load it into data warehouses. Collaborate with data architects and business analysts to define data extraction requirements and transformation rules. ETL Tool Expertise: Utilize Informatica to create ETL mappings, workflows, and transformations, ensuring data quality, accuracy, and timeliness. Develop and optimize complex SQL queries to perform data transformations and manipulation. Data Warehousing: Work closely with the data warehouse team to ensure seamless integration of transformed data into the data warehouse. Implement best practices for data modeling, data integrity, and performance optimization within the data warehouse. Tableau Integration: Integrate ETL processes with Tableau to enable effective data visualization and reporting. Collaborate with Tableau developers to provide well-structured data for various dashboards and reports. Healthcare Domain Knowledge: Apply healthcare industry knowledge to understand data sources, data structures, and domain-specific data transformation requirements. Ensure compliance with healthcare data regulations (HIPAA, HITECH, etc.) throughout the ETL process. Data Quality and Validation: Implement data validation routines to identify and resolve data quality issues during ETL processes. Monitor data quality continuously and proactively address any discrepancies. Documentation: Maintain comprehensive documentation for ETL processes, data mappings, and transformations. Create and update technical documentation for team members and stakeholders. Collaboration and Communication: Collaborate with cross-functional teams including data engineers, analysts, and business stakeholders to understand requirements and deliver solutions.