Data Analyst

Responsibilities Design, develop, and maintain automated data pipelines supporting enterprise healthcare data. Develop and maintain ETL/ELT processes to extract, transform, validate, and load data from multiple sources into standardized target systems. Integrate data from diverse sources, including: Relational and enterprise databases APIs and web services Flat files and structured data files Enterprise applications and other source systems Automate manual data management processes using SQL, Python, and other appropriate technologies to improve operational efficiency, scalability, and data accuracy. Develop and implement data transformation, mapping, standardization, and business rules in collaboration with the Data Quality Team. Develop automated data validation and reconciliation processes to identify: Data discrepancies Duplicate records Missing or incomplete data Invalid values Transformation errors Data integrity issues Support the development and maintenance of a single source of truth by ensuring data is consistent, reliable, standardized, and traceable across enterprise systems. Support Oracle data integration, migration, and data management activities, including: Data extraction Data transformation Data loading Data validation Data reconciliation Develop and maintain data pipeline monitoring, logging, alerting, and error-handling processes to ensure reliable and sustainable data operations. Maintain comprehensive technical and operational documentation for data pipelines, integrations, transformation logic, data mappings, and automated processes. Monitor data pipelines and proactively identify, troubleshoot, and resolve data processing and integration issues. Qualifications Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, Statistics, or a related field; equivalent professional experience may be considered. Experience in data analysis, data engineering, ETL/ELT development, data integration, or a related technical discipline. Strong proficiency in SQL and experience working with relational databases. Experience developing data pipelines and automated data processing workflows. Working knowledge of Python or another programming/scripting language used for data automation. Experience with data extraction, transformation, validation, reconciliation, and loading processes.