Position Title: Senior Analytic Data Engineer (Python/Power BI)
Job Description: 100% Remote
CTH unlikely, but possible; please put salary expectations on resume M-F : 9 to 5
Job Summary:
We are seeking a Senior Analytic Data Engineer to join our technical team, with primary responsibilities spanning the design, development, and maintenance of our organizational data and programming infrastructure for Hedis. This role is critical for establishing and maintaining efficient and reliable data flow across diverse systems feeding our Hedis Engines for regulatory reporting. Core qualifications include a deep understanding of data and ETL architecture, practical experience with cloud-based data platforms (preferably Google Cloud Platform with Databricks/Apache Spark), and strong programming skills in Python/PySpark with direct ETL experience. Additionally, the ideal candidate will possess reporting expertise using Power BI and Tableau, and a proven track record in designing and implementing advanced data engineering solutions, leveraging their full Software Development Life Cycle (SDLC) experience.
Preferred Experience
3 years of experience with data pipeline and workflow management tools (e.g., Apache Spark(Dataproc), Google Cloud Platform Tools, Databricks, PySpark).
3 Years of experience building ETL and Data Integration pipelines in Python, PySpark and knowledge of Informatica is a plus
3 years of experience in a reporting tool like Power BI & Tableau. (Power BI preferred)
3 years of experience working with On Prem databases like Oracle, Teradata and DB2
3 years of experience with Cloud platforms (Google Cloud Platform and Azure) and their respective data services
3 years of deep SQL experience & Unix experience
3 years of experience working with a variety of technology systems, designing solutions or developing data solutions in healthcare. Hedis experience is a big plus.
3 years of experience translating requirements, design mockups, prototypes or user stories into technical designs
3 years of experience with data-related code that is fault-tolerant, efficient, and maintainable
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