Staff Software Engineer, Data Engineering

Docker
Seattle; Washington, US
On-site

Job Description

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.

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 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 rota

Skills & Requirements

Technical Skills

SnowflakeAwsAirflowDbtSigmaData pipelinesData transformationsData modelingData orchestrationData apisSelf-service analyticsIntegration with downstream systemsTechnical leadershipMentorshipHiringTechnical assessmentStrategic thinkingCollaborationRequirements engineeringMentoringKnowledge sharingEngineering excellenceData engineeringData infrastructureData analytics

Employment Type

FULL TIME

Level

senior

Posted

4/23/2026

Apply Now

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