Staff Software Engineer, Data Engineering

About the Role

Docker, with its 20 million monthly users and 20 billion image pulls, is the number one tool for building, sharing, and running apps, trusted by startups and Fortune 100s alike. This role is pivotal in scaling Docker's data capabilities as the company continues to expand its product portfolio and serve enterprise customers worldwide.

The team context for this role involves close collaboration with cross-functional teams to understand requirements and deliver data solutions that drive business outcomes. The reporting structure for this position will likely involve working closely with senior leaders in the data organization and other stakeholders across the company.

What You Will Do

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

What We Are Looking For

• Expert-level technical skills in modern data platforms.
• Strong system design capabilities.
• Ability to influence technical direction while mentoring and developing other engineers.
• Experience with Snowflake, AWS, Airflow, DBT, and Sigma.
• Proficiency in designing and implementing scalable data infrastructure.
• Strong understanding of data quality, testing, monitoring, and operational excellence principles.
• Experience with data orchestration workflows and data API development.
• Excellent collaboration and communication skills.
• Ability to work in a remote-first environment.

Nice to Have

• Experience with Excel for data analysis and reporting.
• Knowledge of machine learning and business intelligence principles.
• Familiarity with Docker's products and services.
• Experience working in a fast-paced, rapidly scaling company.
• Certification in data engineering or a related field.

Benefits and Perks

• Competitive compensation package.
• Equity in a rapidly growing company.
• Comprehensive health, dental, and vision insurance.
• Flexible PTO policy.
• Remote work stipend.
• Opportunities for professional development and growth.
• Access to the latest technologies and tools.
• Collaborative, dynamic work environment.

• Leverage your Excel skills: Highlight any experience with Excel for data analysis, as it's a valuable asset in this role.
• Showcase data infrastructure projects: Include any personal or professional projects that demonstrate your ability to design and implement scalable data infrastructure.
• Prepare for technical interviews: Review modern data platforms, system design principles, and be ready to discuss your experience with technologies like Snowflake and AWS.
• Emphasize collaboration skills: Docker values collaboration; be prepared to give examples of how you've worked effectively with cross-functional teams.
• Research Docker's products and mission: Understand Docker's role in the industry and how your skills can contribute to its mission.
• Highlight leadership and mentorship experience: As a Staff Software Engineer, you'll be expected to mentor and lead other engineers; be prepared to discuss your approach to technical leadership.
• Be ready to discuss data quality and operational excellence: Docker emphasizes the importance of data quality and operational excellence; be prepared to share your strategies for ensuring these aspects in your work.