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.

Responsibilities

Technical Strategy & Architecture Leadership

• Define and drive the technical strategy for Docker's data platform architecture, establishing long-term vision for scalable data systems

• Lead design and implementation of highly scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and Sigma

• Architect end-to-end data pipelines supporting real-time and batch analytics across Docker's product ecosystem

• Drive technical decision-making around data platform technologies, architectural patterns, and engineering best practices

• Establish technical standards for data quality, testing, monitoring, and operational excellence

Hands-On Engineering & System Development

• Design and build robust, scalable data systems that process petabytes of data and support millions of user interactions

• Implement complex data transformations and modeling using DBT for analytics and business intelligence use cases

• Develop and maintain sophisticated data orchestration workflows using Apache Airflow

• Optimize Snowflake performance and cost efficiency while ensuring reliability and scalability

• Build data APIs and services that enable self-service analytics and integration with downstream systems

Cross-Functional Collaboration & Requirements Engineering

• Partner with Product, Engineering, and Business teams to understand analytics requirements and translate them into technical solutions

• Collaborate with Data Scientists and Analysts to enable advanced analytics, machine learning, and business intelligence capabilities

• Work with Finance, Sales, and Marketing teams to deliver accurate reporting and operational dashboards

• Support customer-facing analytics initiatives and embedded reporting capabilities

• Engage with Security and Compliance teams to ensure data governance and regulatory requirements are met

Technical Operations & Reliability

• Own operational excellence for critical data systems including monitoring, alerting, and incident response

• Implement comprehensive data quality frameworks and automated testing for data pipelines and transformations

• Drive performance optimization and cost management initiatives across the data platform

• Establish disaster recovery and business continuity procedures for business-critical data systems

• Lead troubleshooting and resolution of complex technical issues affecting data availability and accuracy

Mentorship & Technical Leadership

• Mentor junior and mid-level engineers on technical skills, system design, and data engineering best practices

• Conduct technical design reviews and provide guidance on ar