• Design and implement scalable, high-performance data architectures across cloud and hybrid environments • Define and enforce data modeling standards, including conceptual, logical, and physical data models • Build and optimize enterprise data pipelines and data integration frameworks to support analytics and operational use cases • Architect and manage data platforms leveraging technologies such as Snowflake, Databricks, Spark, and Azure Data services • Collaborate with data engineers, data scientists, and business stakeholders to translate business needs into robust data solutions • Establish and maintain data governance, data quality, and metadata management frameworks • Ensure data privacy, security, and compliance requirements are met across all platforms and pipelines • Lead architecture decisions for data storage solutions including data lakes, data warehouses, and real-time data processing systems • Optimize performance and cost efficiency of data platforms and workloads • Support Agile delivery frameworks and contribute to sprint planning, backlog grooming, and architectural roadmaps • Implement and oversee CI/CD pipelines and infrastructure-as-code practices for data solutions • Evaluate emerging technologies and recommend solutions to enhance data capabilities

• Assemble large, complex data sets that meet business requirements through extraction, transformation, and loading of data from a wide variety of data sources. • Provide operational support and troubleshooting for existing processes and systems. • Work closely with architects, solution leads, data owners, Data Scientists and key stakeholders to facilitate and coordinate the data platform backlog grooming process, triaging new feature requests in preparation for future project activities. • Deliver automation & efficient processes to ensure high quality throughput & performance of the entire data & analytics platform. • Ensure data extraction, transformation and loading data meet data security & compliance requirements. • Engage with data source platform leads to gain tactical and strategic understanding of data sources required by Agency Data Services AI/ML as well as Data Office standards. • Create data tools for data scientist team members that assist them in building and optimizing models.

• Lead the end-to-end development of an internal-facing GenAI capability • Conduct competitive scans of the emerging Databricks ecosystem and adjacent tooling • Help define schemas, APIs, and contracts • Participate in biweekly Data Platform demos and engineering standups • Close collaboration and weekly 1:1s with the Principal Product Manager of Data Platform.

• Own the Data Governance & Accessibility program • Design scalable data architecture • Improve pipeline reliability and mentor data engineers