Note: The job is a remote job and is open to candidates in USA. Docker, Inc. is a developer tooling company providing products and infrastructure for building, sharing, and running applications. Docker is seeking a Senior Software Engineer to design and build scalable data infrastructure, pipelines, APIs, and analytics systems while establishing technical standards, ensuring reliability, and mentoring engineers. The role partners with cross-functional teams to enable data-driven decision-making, advanced analytics, business intelligence, and reporting.

Responsibilities

• Architect and implement key components of Docker's data platform, driving technical direction for the team
• Design and build scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and Sigma
• Build end-to-end data pipelines supporting real-time and batch analytics across the product ecosystem
• Evaluate and select data platform technologies, architectural patterns, and engineering best practices
• Apply and help improve technical standards for data quality, testing, monitoring, and operational excellence
• Build high-throughput data systems supporting high-volume user interactions
• Develop data transformations and models using DBT for analytics and business intelligence
• Develop and maintain data orchestration workflows using Apache Airflow
• Optimize Snowflake performance and cost efficiency while ensuring reliability and scalability
• Build data APIs and services enabling self-service analytics and downstream integrations
• Translate business and product analytics requirements into technical solutions
• Collaborate with Data Scientists and Analysts to enable advanced analytics, ML, and BI capabilities
• Work with Finance, Sales, and Marketing teams to deliver accurate reporting and operational dashboards
• Support customer-facing analytics initiatives and embedded reporting capabilities
• Partner with Security and Compliance to ensure data governance and regulatory compliance
• Ensure system reliability, monitoring, alerting, and incident response for owned components
• Implement data quality checks and automated testing for data pipelines and transformations
• Optimize performance and manage infrastructure costs across the data platform
• Establish disaster recovery and business continuity procedures for critical data systems
• Lead troubleshooting and resolution of complex technical issues affecting data availability and accuracy
• Mentor engineers on system design, technical execution, and data engineering best practices
• Conduct technical design reviews and provide actionable feedback on software architecture
• Contribute to knowledge sharing through documentation, tech talks, and cross-team collaboration
• Model engineering excellence practices within the data team
• Participate in hiring and technical assessment processes for data engineering roles

Skills

• 6+ years of software engineering experience, with 3+ years focused on data engineering
• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• Strong experience with Snowflake, including SQL tuning, performance optimization, and cost management
• Proficiency with DBT for data modeling, transformation, and testing at production scale
• Experience orchestrating workflows and pipelines with Apache Airflow
• Experience using Sigma or similar modern BI platforms for self-service analytics
• Production experience with AWS data services (S3, Redshift, EMR, Glue, Lambda, Kinesis)
• Proficiency in Python and SQL for data engineering applications
• Experience with Infrastructure-as-Code, CI/CD pipelines, and modern DevOps practices
• Track record of designing and building large-scale distributed data systems
• Solid understanding of data warehousing, dimensional modeling, and analytics architectures
• Experience with stream processing, event-driven architectures, and real-time data systems
• Understanding of data governance, security standards, and privacy frameworks (e.g., GDPR, CCPA)
• Proven track record optimizing performance and cost for cloud data infrastructure
• Ability to guide technical choices through sound engineering judgment
• Experience mentoring engineers and leading technical projects without direct management authority
• Clear written and verbal communication skills, tailored to technical and non-technical stakeholders
• Proven ability to collaborate effectively with Product, Business, and Engineering partners
• 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 such as GCP or 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 a related technical field
• Experience with customer-facing analytics and embedded reporting solutions
• Knowledge of financial data systems and revenue analytics

Benefits

• Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.
• Flexibility that fits your life – We trust you to manage your schedule while delivering great work.
• Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.
• Home office support – Set up your workspace for comfort and success.
• Technology stipend – Equivalent to US$100 net per month to help support your work.
• Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.
• Parental leave – 16 weeks of paid parental leave after six months of employment.
• Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.
• Comprehensive benefits – Medical, retirement, and paid holidays vary by country.
• Docker swag – Because representing the whale never gets old.

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