Staff Software Engineer, Data Engineering

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.

We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.

Docker is seeking a Staff Software Engineer to join our Data Engineering 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.

• 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

• 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

• 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

• 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

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

• Conduct technical design reviews and provide guidance on architectural decisions

• Drive knowledge sharing initiatives including documentation, tech talks, and cross-team collaboration

• Establish and promote engineering excellence practices across the data organization

• Contribute to hiring and technical assessment processes for data engineering roles

• Take part in on-call rotation for your team; respond to incidents, debug production issues, and drive continuous improvement of system reliability

• 8+ years of software engineering experience with 3+ years focused on data engineering and analytics systems

• Proven track record designing and implementing large-scale distributed data systems

• Deep understanding of data warehousing concepts, dimensional modeling, and analytics architectures

• Experience with stream processing, event-driven architectures, and real-time data systems

• Knowledge of data governance, security frameworks, and compliance requirements (GDPR, CCPA)

• Strong background in performance optimization and cost management for cloud data platforms

• Demonstrated ability to drive technical strategy and influence engineering decisions across teams

• Experience mentoring engineers and leading technical initiatives without direct management authority

• Excellent communication skills with ability to explain complex technical concepts to diverse audiences

• Track record of successful cross-functional collaboration with Product, Business, and Executive stakeholders

• Experience establishing technical standards and driving adoption across engineering organizations

• Experience at high-growth technology companies, particularly in developer tools or infrastructure software

• Background with container technologies, Kubernetes, or cloud-native development

• Knowledge of machine learning platforms and MLOps practices

• Experience with additional cloud platforms (GCP, Azure) and multi-cloud data strategies

• Familiarity with modern data catalog tools, metadata management, and data lineage systems

• Advanced degree in Computer Science, Data Engineering, or related technical field

• Experience with customer-facing analytics and embedded reporting solutions

• Knowledge of financial data systems and revenue analytics

• Successful design and delivery of scalable data systems supporting company-wide analytics needs

• System reliability and performance metrics meeting enterprise SLA requirements

• Cost optimization achievements for data infrastructure while maintaining performance

• Technical mentorship effectiveness measured by team growth and knowledge transfer

• Cross-functional stakeholder satisfaction with data platform capabilities and reliability

• Contribution to data engineering best practices and technical standards adoption

As a Staff Software Engineer in our Data group, you'll be instrumental in building the data foundation that powers Docker's product innovation and business intelligence. You'll architect and implement systems that enable teams across Docker to make data-driven decisions while creating analytics capabilities that differentiate our products in the market. Your technical leadership will be critical to scaling Docker's data infrastructure as we continue to expand our product portfolio and serve enterprise customers globally.

You'll have the opportunity to work on challenging technical problems at scale while directly influencing Docker's data strategy and mentoring the next generation of data engineers. Your contributions will enable millions of developers to build better software through the insights and capabilities your data systems provide.

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