Docker is seeking a Staff Software Engineer to lead the design, development, and implementation of scalable data systems. The ideal candidate will have expertise in Snowflake, AWS, and data engineering principles.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
About The Company
Docker, Inc. is a leading provider of containerization and developer productivity tools that revolutionize the way applications are built, shared, and run. With a global remote-first team, Docker empowers developers and enterprises worldwide to streamline their software development lifecycle. Trusted by over 20 million monthly users and responsible for more than 20 billion image pulls, Docker has established itself as the industry standard for containerization technology. The company’s mission is to simplify application deployment, foster innovation, and enable scalable, secure, and efficient software ecosystems. As Docker continues to grow rapidly, it remains committed to fostering a diverse and inclusive environment where talent and innovation thrive.
About The Role
We are seeking a highly skilled Staff Software Engineer specializing in Data Engineering to join our dynamic Data Engineering team. In this pivotal role, you will lead the design, development, and implementation of scalable data systems that support analytics and business intelligence across the entire organization. As Docker scales its operations to serve millions of developers and thousands of enterprise clients globally, your expertise will be crucial in architecting robust data infrastructure that enables data-driven decision-making. This role combines hands-on technical contribution with strategic leadership, mentorship, and cross-functional collaboration. You will work closely with product, engineering, sales, marketing, finance, and executive teams to understand their data needs and deliver innovative solutions that drive business growth and operational excellence.
Qualifications
- 6+ years of software engineering experience, with at least 3+ years focused on data engineering and analytics systems
- Expert-level proficiency with Snowflake, including SQL, performance tuning, and cost management
- Deep experience with DBT for data modeling, transformation, and testing in large-scale environments
- Strong expertise in Apache Airflow for complex workflow orchestration
- Hands-on experience with modern BI platforms such as Sigma or similar tools
- Extensive AWS experience, including services like S3, Redshift, EMR, Glue, Lambda, and Kinesis
- Proficiency in Python, SQL, and other relevant programming languages
- Solid understanding of data warehousing concepts, distributed systems, and analytics architecture
- Experience with stream processing, real-time data systems, and event-driven architectures
- Knowledge of data governance, security standards, and compliance frameworks (GDPR, CCPA)
- Strong leadership skills with a proven ability to influence technical decisions and mentor engineers
- Excellent communication skills to collaborate effectively across teams and stakeholders
Responsibilities
- Define and execute the technical strategy for Docker’s data platform, establishing a long-term vision for scalable data systems
- Lead the design and implementation of high-performance, scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and Sigma
- Architect end-to-end data pipelines supporting both real-time and batch analytics across various product ecosystems
- Make strategic technical decisions regarding data platform technologies, architectural patterns, and best practices
- Establish standards for data quality, testing, monitoring, and operational excellence to ensure reliability and accuracy
- Design and develop robust data systems capable of processing petabytes of data and supporting millions of user interactions
- Implement complex data transformations and modeling for analytics and business intelligence use cases
- Optimize Snowflake performance and cost efficiency while maintaining system reliability
- Create data APIs and services that enable self-service analytics and integration with downstream systems
- Collaborate with cross-functional teams to gather requirements and translate them into scalable technical solutions
- Partner with data scientists and analysts to facilitate advanced analytics, machine learning, and reporting capabilities
- Support operational data needs for finance, sales, and marketing teams with accurate dashboards and reports
- Ensure compliance and data governance standards are met, working with security teams as needed
- Own operational responsibilities including monitoring, incident response, and disaster recovery planning
- Mentor junior and mid-level engineers, conducting design reviews and promoting engineering best practices
- Drive knowledge sharing initiatives and contribute to the continuous improvement of data engineering standards
Benefits
- Flexible work arrangements to support work-life balance
- Designated quarterly Whaleness Days for focused innovation and team bonding
- Home office setup support to ensure a comfortable remote working environment
- Paid parental leave of up to 16 weeks
- Technology stipend of $100 net per month to support work-related needs
- Generous PTO policy encouraging employees to take time off and recharge
- Quarterly company-wide hackathons fostering innovation and collaboration
- Training stipends for conferences, courses, and professional development
- Equity options to share in the company's growth and success
- Company swag and branded merchandise
- Comprehensive medical benefits, retirement plans, and holiday policies, varying by country
Equal Opportunity
Docker, Inc. is an equal opportunity employer committed to fostering an inclusive environment. We celebrate diversity and are dedicated to building a team that reflects a variety of backgrounds, perspectives, and skills. We do not discriminate based on race, gender, age, religion, sexual orientation, disability, or any other protected status.