Staff Software Engineer, Data Infrastructure Job at Docker (Seattle)

Staff Software Engineer, Data Infrastructure

Docker

Location:
United States , Seattle

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

195400.00 - 275550.00 USD / Year

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Job Description:

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.

Job Responsibility:

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

Requirements:

8+ years of software engineering experience with 3+ years focused on data engineering and analytics systems
Expert-level experience with Snowflake including advanced SQL, performance optimization, and cost management
Deep proficiency in DBT for data modeling, transformation, and testing with experience in large-scale implementations
Strong expertise with Apache Airflow for complex workflow orchestration and pipeline management
Hands-on experience with Sigma or similar modern BI platforms for self-service analytics
Extensive AWS experience including data services (S3, Redshift, EMR, Glue, Lambda, Kinesis) and infrastructure management
Proficiency in Python, SQL, and other programming languages commonly used in data engineering
Experience with infrastructure-as-code, CI/CD practices, and modern DevOps tools
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
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

Nice to have:

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

What we offer:

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity
we are a growing start-up and want all employees to have a share in the success of the company
Docker Swag
Medical benefits, retirement and holidays vary by country
Remote-first culture, with offices in Seattle and Paris

Additional Information:

Job Posted:
February 21, 2026

Employment Type:

Fulltime

Work Type:

Remote work

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