Staff Software Engineer, Data Infrastructure

At Docker, we make app development easier so developers can focus on what matters. Our remote-first team spans the globe, united by a passion for innovation and great developer experiences. With over 20 million monthly users and 20 billion image pulls, Docker is the #1 tool for building, sharing, and running apps—trusted by startups and Fortune 100s alike. We’re growing fast and just getting started. Come join us for a whale of a ride!Docker is seeking a Staff Software Engineer to join our Data Infrastructure team and drive the technical evolution of data systems that power analytics across the entire company. As Docker continues to scale with millions of developers and thousands of enterprise customers globally, we need a senior technical leader who can design, build, and launch scalable data infrastructure that enables data-driven decision making across Product, Engineering, Sales, Marketing, Finance, and Executive teams.This is a hands-on technical leadership role combining deep individual contribution with strategic thinking and mentorship responsibilities. You'll be responsible for architecting and implementing robust data systems and processes that support Docker's analytic needs while establishing technical standards and best practices for the data organization. You'll work closely with cross-functional teams to understand requirements and deliver data solutions that drive business outcomes.Success in this role requires expert-level technical skills in modern data platforms, strong system design capabilities, and the ability to influence technical direction while mentoring and developing other engineers. You'll play a critical role in scaling Docker's data capabilities as we continue to expand our product portfolio and serve enterprise customers worldwide. ResponsibilitiesTechnical Strategy & Architecture LeadershipDefine and drive the technical strategy for Docker's data platform architecture, establishing long-term vision for scalable data systemsLead design and implementation of highly scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and SigmaArchitect end-to-end data pipelines supporting real-time and batch analytics across Docker's product ecosystemDrive technical decision-making around data platform technologies, architectural patterns, and engineering best practicesEstablish technical standards for data quality, testing, monitoring, and operational excellenceHands-On Engineering & System DevelopmentDesign and build robust, scalable data systems that process petabytes of data and support millions of user interactionsImplement complex data transformations and modeling using DBT for analytics and business intelligence use casesDevelop and maintain sophisticated data orchestration workflows using Apache AirflowOptimize Snowflake performance and cost efficiency while ensuring reliability and scalabilityBuild data APIs and services that enable self-service analytics and integration with downstream systemsCross-Functional Collaboration & Requirements EngineeringPartner with Product, Engineering, and Business teams to understand analytics requirements and translate them into technical solutionsCollaborate with Data Scientists and Analysts to enable advanced analytics, machine learning, and business intelligence capabilitiesWork with Finance, Sales, and Marketing teams to deliver accurate reporting and operational dashboardsSupport customer-facing analytics initiatives and embedded reporting capabilitiesEngage with Security and Compliance teams to ensure data governance and regulatory requirements are metTechnical Operations & ReliabilityOwn operational excellence for critical data systems including monitoring, alerting, and incident responseImplement comprehensive data quality frameworks and automated testing for data pipelines and transformationsDrive performance optimization and cost management initiatives across the data platformEstablish disaster recovery and business continuity procedures for bu ... (truncated, view full listing at source)