Tableau, Python Developer

Job Description: Be the hands-on technical lead for dashboard, reporting, and data engineering work within a large-scale Medicaid EDW and analytics program.Design, develop, and maintain enterprise-level dashboards and reports using Tableau and Python-based frameworks, ensuring they're performant, reusable, and built to last.Build and optimize scalable data processing pipelines using Python, supporting both ongoing analytics needs and federal reporting requirements.Write and tune SQL and stored procedures across relational platforms — primarily Teradata — with a focus on accuracy and efficiency at enterprise scale.Support Medicaid analytics and federal reporting initiatives including T-MSIS, PERM, MARS, and Quality of Care programs, working closely with SMEs and compliance teams.Participate in cloud migration and modernization work within Azure-based architectures, contributing to the shift from legacy systems toward modern platforms.Collaborate with analysts, QA teams, and BI reporting leads to validate data quality, resolve discrepancies, and ensure timely delivery of reporting deliverables.Support production operations — including incident response and root-cause analysis — and contribute to a stable, reliable analytics environment.Participate in code reviews, maintain source control hygiene, and work within CI/CD processes using Azure DevOps and GitHub.Requirements: 5+ years of experience in enterprise reporting and dashboard development, with a strong focus on Tableau and Business Objects5+ years of hands-on Python development for data engineering and automation3+ years working with Spark-based processing frameworks such as DatabricksStrong SQL expertise with experience in relational databases including Teradata, Snowflake, Oracle, or SQL ServerDemonstrated experience with source control and DevOps practices — Azure DevOps, GitHub, CI/CD pipelinesBachelor's degree in Computer Science, Engineering, Analytics, or a related fieldStrong analytical and troubleshooting skills, with a track record of solving complex data problems in regulated environments.Benefits: Mission-driven impact at scale.Autonomy on meaningful problems.Data & innovation at the center.Collaborative, delivery-focused culture.Public health improvement.