• Designing, developing, and optimizing high-performance data plane software using modern C/C++ on Linux-based systems • Developing networking software for DPU-based Smart Switch platforms • Troubleshooting complex software defects, networking issues, and customer-reported problems • Leading technical design discussions and participating in architecture and code reviews • Collaborating with cross-functional engineering teams to deliver innovative networking and security capabilities

• Act as the liaison between Line of Business Units and Data Protection engineers to establish new Data Protection policies and rules and/or rule refinement • Support the Data Protection product owner defining the intent, roadmap, and strategy to ensure execution and delivery of the data protection and data discovery roadmap. • Acting as a subject matter expert to assist with solving data protection challenges • Develop, define, and maintain Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) to measure, monitor, and report on the effectiveness of data protection controls, facilitating continuous risk mitigation. • Collaborate with key stakeholders to create and maintain dashboards in Tableau that visualize KPIs and KRIs, providing actionable insights into data protection performance.

• Shape the pipelines and integrations feeding our RCT platform and our foundational voter datasets: the APIs, replication, federation layers, experiment randomization, and the failure modes that come with running data systems for hundreds of partner organizations on a non-negotiable political calendar • Extend our data platform and orchestration layer, and optimize it for cost, runtime, and reliability so it holds up during the elections, with millions of outreach attempts • Lead projects that span multiple systems and teams — scoping, designing, and driving them to real milestones • Hold the bar on quality — test and validate your own work, review teammates' code, and mentor through that review • Document and communicate — make your systems understandable to teammates, stakeholders, and non-engineers • Rotate through on-call and rapid response, including evenings and weekends during high-stakes moments like election cycles

• Define and maintain data architecture standards, principles, patterns, and best practices across key business and data domains. • Assess and rationalize critical data sources based on business value, quality, ownership, usage, sensitivity, lifecycle, and strategic importance. • Design conceptual, logical, and physical data models that support operational systems, analytical platforms, reporting, data products, and integration needs. • Establish reusable data structures, canonical data models, reference data patterns, and integration approaches to improve consistency across systems. • Define architecture patterns for data ingestion, transformation, storage, consumption, sharing, retention, and lifecycle management. • Partner with data engineering teams to translate architecture into scalable pipelines, curated datasets, data marts, reusable services, and platform-ready data assets. • Drive standards for metadata, lineage, business definitions, data ownership, data quality rules, documentation, and data observability. • Support governance practices by helping define how data should be classified, secured, cataloged, retained, and accessed. • Work with application and platform teams to improve interoperability across source systems, APIs, data warehouses, data lakes, lakehouses, and cloud platforms. • Guide teams in designing reusable and trusted data assets that can serve multiple consumption patterns, including reporting, analytics, automation, machine learning, and AI-enabled solutions. • Provide architecture guidance during solution design, data quality investigations, platform modernization, and data integration initiatives. • Communicate architecture decisions, tradeoffs, standards, and design recommendations clearly to technical teams and senior stakeholders. • All other duties as assigned