• Design, build, and maintain scalable, reliable, and secure data pipelines using Python, with a focus on enabling data access and insight across product teams, engineering, and entities. • Develop reusable data services and frameworks that support high-quality data ingestion, transformation, and ML model deployment — accelerating analytics and experimentation across the organization. • Collaborate with data scientists and ML engineers to productionize machine learning workflows using SageMaker, Vertex AI, or other MLOps tools • Implement monitoring, testing, and CI/CD automation for data pipelines and ML services • Own and evolve real-time and batch data integrations between ActBlue’s core systems and user-facing applications — influencing design decisions and architecture across multiple teams including Product, Engineering, and Analytics. • Develop, optimize and support reverse ETL workflows using tools like Hightouch • Participate in code reviews, mentor junior engineers, and help foster a high-trust engineering culture. • Demonstrate technical leadership through writing documentation, establishing effective monitoring, and fostering clear and audience-oriented communication.