Python Developer (Analytics & Modernization)

Job Title: Senior Python Developer (Analytics & Modernization)Experience: 8+ Years USALocation: RemoteJob SummaryWe are seeking a highly skilled Senior Python Developer to lead the modernization of our data and analytics ecosystem. You will be a key driver in migrating legacy SAS environments to modern R/Python infrastructures, refactoring complex codebases, and establishing scalable data processing solutions. The ideal candidate will bridge the gap between business requirements and technical execution, providing both hands-on development and high-level architectural support for our analytics teams.Key ResponsibilitiesAnalytics Modernization: Lead and execute migration initiatives, converting legacy SAS programs and macros into high-performance, modular Python or R scripts. Data Pipeline Development: Design, build, and maintain robust Python-based data processing, automation, and analytics pipelines. Environment Administration: Support and manage Posit / RStudio environments to ensure seamless access and scalability for data science teams. Code Refactoring: Evaluate existing legacy code for optimization opportunities, ensuring new solutions adhere to modern security and performance standards. Cross-Functional Collaboration: Partner with business stakeholders and analytics teams to translate complex requirements into scalable technical architectures. User Support: Provide technical guidance and troubleshoot issues for analytics platform users as needed. Required Skills & ExperienceCore Technical Expertise: 8+ years of software development experience with deep proficiency in Python for data engineering and analytics. Migration Background: Proven experience leading SAS to R/Python migration projects, including translating SAS DATA steps and PROC SQL into open-source alternatives. Database Mastery: Expert-level knowledge of SQL and relational database design. Analytics Ecosystems: Hands-on experience supporting and managing Posit (formerly RStudio) or similar centralized data science environments. Modern DevOps: Proficiency with Git for version control and familiarity with CI/CD practices to ensure code quality and security. Analytical Mindset: Strong ability to perform complex data analysis and ensure statistical reproducibility during the migration process. Nice-to-Have SkillsExperience with cloud data platforms (AWS, Snowflake, or Databricks). Familiarity with containerization (Docker/Kubernetes). Relevant technical certifications in Python, R, or Cloud Architecture. Educational QualificationsBachelor s or Master s degree in Computer Science, Engineering, Mathematics, or a related technical field (BE/ME, BTech/MTech, BSc/MSc).