Job Summary: We are seeking an experienced ETL (Extract, Transform, Load) Developer to join our Regional Data Integration Team. As an ETL Developer, you will be responsible for designing, developing, testing, and implementing ETL processes to extract data from multiple sources, transform it into a usable format, and load it into a target database. You will work closely with the business stakeholders and the data analysts to ensure that the data is accurate, timely, and of high quality.
Responsibilities: Design, develop, test, and implement ETL processes to extract data from multiple sources, transform it into a usable format, and load it into a target database. Work with the business stakeholders and data analysts to understand the data requirements and design ETL processes accordingly. Create and maintain technical documentation for ETL processes. Monitor and troubleshoot ETL processes to ensure that they run smoothly and efficiently. Develop and maintain ETL schedules and workflows. Perform data profiling, data mapping, and data quality analysis to ensure that the data is accurate and of high quality. Ensure data security and privacy by implementing appropriate access controls and encryption techniques. Stay up to date with the latest ETL tools and technologies and recommend improvements to the existing ETL processes. Qualifications: Bachelor's degree in Computer Science, Information Systems, or a related field. 4+ years of experience in ETL development. Strong knowledge of ETL tools and technologies such as Informatica, Talend, SSIS, etc. Experience in designing and developing complex ETL processes. Strong SQL and database skills. Experience working with large datasets. Experience with Object Oriented Programming in Python or Java. Experience with REST API interfaces. Strong problem-solving and analytical skills. Excellent communication and collaboration skills. Ability to work independently as well as in a team environment. Knowledge of data warehousing concepts and methodologies. Knowledge of healthcare industry data standards and data models. Strong ties to data governance and data lineage. Quality driven implementation.
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