Who you are

• 8+ years of hands-on experience in data engineering, analytics engineering, or related technical roles
• 3+ years in senior technical leadership positions (Staff Engineer, Principal Engineer, or equivalent)
• Experience designing and scaling data systems for companies with 100M+ users or equivalent scale
• Experience guiding technical teams and facilitating cross-functional engineering initiatives
• Expert-level proficiency in modern data stack technologies (dbt, Snowflake/BigQuery/Databricks, Apache Airflow/Prefect)
• Strong programming skills in Python, SQL, and at least one additional language (Scala, Java, Go, or Rust)
• Deep understanding of distributed systems, data modeling, and database optimization techniques
• Experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform, CloudFormation)
• Knowledge of streaming data technologies (Kafka, Kinesis, Pub/Sub) and real-time analytics
• Demonstrated ability to influence technical decisions across multiple engineering teams
• Strong written and verbal communication skills, with ability to explain complex technical concepts to non-technical stakeholders
• Experience mentoring and developing senior engineering talent
• Track record of successfully delivering large-scale, multi-quarter technical initiatives
• Understanding of SaaS business models, customer analytics, and revenue operations
• Experience with product analytics, user behavior analysis, and A/B testing frameworks
• Knowledge of data privacy regulations (GDPR, CCPA) and enterprise compliance requirements
• Experience at high-growth technology companies or developer-focused platforms
• Background in containerization technologies, Docker ecosystem, or developer tools
• Experience with machine learning infrastructure and MLOps practices
• Previous experience in marketplace, multi-tenant, or developer platform environments
• Advanced degree in Computer Science, Data Science, or related technical field
• Industry certifications (AWS Solutions Architect, dbt, Snowflake Pro, etc.)

What the job involves

• Docker is seeking an exceptional Principal Data Engineer to lead the technical vision and architecture of our Data organization within our infrastructure group
• This role will address critical data strategy challenges, building and launching scalable software systems and processes to unlock data at Docker
• You will drive technical leadership across data infrastructure, analytics platforms, and revenue-enabling data products while mentoring senior engineers and collaborating with stakeholders across the company
• As a Principal Engineer, you will be responsible for solving Docker's most complex data engineering challenges at scale, architecting systems that support millions of developers and containers, and establishing data governance frameworks that enable rapid business growth and decision-making
• Define and drive the long-term technical strategy for Docker's data platform, addressing current fragmentation across disparate data sources
• Architect scalable, reliable data infrastructure supporting Docker's growing customer base and container ecosystem
• Lead cross-functional technical discussions to align on data architecture decisions
• Establish technical standards and best practices across data engineering, analytics engineering, and data science teams
• Design and implement data governance frameworks that ensure quality, security, and compliance (SOC-2, privacy regulations)
• Own the design of mission-critical data pipelines supporting customer usage measurement, billing systems, and revenue operations
• Build robust ETL/ELT frameworks capable of processing Docker's container telemetry, user analytics, and business metrics at scale
• Architect Customer 360 data models that unify user behavior, account information, and product usage across Docker's platform
• Design monitoring, alerting, and observability systems for data infrastructure health and reliability
• Lead integration efforts with third-party tools (CRM, ERP, analytics platforms) and internal Docker services
• Partner with business stakeholders to translate complex business requirements into scalable technical solutions
• Drive data-driven decision making by establishing clear metrics, dashboards, and KPIs aligned with business objectives
• Lead strategic initiatives that unlock new revenue streams through improved data capabilities and insights
• Establish processes that reduce time-to-insights from months to weeks for critical business questions
• Create data architecture that enables Docker's expansion into new markets and customer segments
• Provide technical mentorship to senior data engineers, analytics engineers, and data scientists
• Lead architectural reviews, code reviews, and technical decision-making processes
• Drive hiring and technical interview processes for senior data team members
• Foster a culture of operational excellence, data quality, and technical innovation
• Collaborate with Engineering Leadership on team roadmaps, prioritization, and resource allocation
• Partner with Product, Sales, Marketing, and Customer Success teams to understand and address their data needs
• Work closely with Security and Compliance teams to ensure data handling meets enterprise requirements
• Collaborate with Platform engineering teams on shared infrastructure and tooling
• Engage with Finance and Legal teams on data governance, retention, and privacy requirements

Benefits

• 100% company paid medical premiums for employees and dependents
• Flexible Time Off Policy
• “Whaleness” Days — At least 1 company wide day off per month
• Employer Paid Holidays
• Generous Maternity and Parental Leave
• Home Office Set Up Budget
• Monthly Technology Stipend
• Training Allowances
• Life and Disability Insurance
• Retirement Plans
• Virtual and In-Person Social Events
• Docker Swag
• Quarterly Hackathons
• Virtual Coffee with Co-Workers