Senior Software Engineer, Data Infrastructure

Responsibilities

• Architect and implement key components of Docker’s data platform while driving technical direction and engineering standards.
• Build scalable real-time and batch data pipelines, high-throughput data systems, data transformations, models, orchestration workflows, and data APIs.
• Use Snowflake, DBT, Apache Airflow, AWS, and Sigma to support analytics, business intelligence, and self-service reporting.
• Optimize data platform performance, reliability, scalability, and infrastructure costs, including monitoring, alerting, incident response, testing, disaster recovery, and business continuity.
• Translate analytics and product requirements into technical solutions and collaborate with cross-functional business, product, engineering, finance, sales, marketing, data science, and analyst stakeholders.
• Ensure data governance, security, privacy, regulatory compliance, data quality, and operational excellence.
• Mentor engineers, conduct technical design reviews, provide architecture feedback, share knowledge, and participate in hiring and technical assessments.

Requirements

• 6+ years of software engineering experience, including 3+ years focused on data engineering.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Strong production experience with Snowflake, including SQL tuning, performance optimization, and cost management.
• Proficiency with DBT, Apache Airflow, Python, and SQL for production-scale data engineering.
• Experience with Sigma or similar modern BI platforms and AWS data services including S3, Redshift, EMR, Glue, Lambda, and Kinesis.
• Experience with infrastructure-as-code, CI/CD pipelines, and modern DevOps practices.
• Experience designing large-scale distributed data systems, data warehouses, dimensional models, analytics architectures, stream processing, event-driven architectures, and real-time data systems.
• Understanding of data governance, security standards, and privacy frameworks such as GDPR and CCPA.
• Experience optimizing cloud data infrastructure performance and cost, mentoring engineers, leading technical projects without direct management authority, and collaborating with technical and non-technical stakeholders.
• Preferred qualifications include experience in high-growth technology or developer-tool companies, container technologies, Kubernetes, cloud-native development, machine learning platforms, MLOps, GCP, Azure, multi-cloud data strategies, data catalogs, metadata management, data lineage, advanced technical education, customer-facing analytics, embedded reporting, financial data systems, and revenue analytics.

Benefits

• Remote-first work-from-home model with offices in Seattle and Paris for collaboration.
• Flexible scheduling, generous PTO, quarterly Whaleness Days, and an end-of-year Whaleness break.
• Home-office support and a technology stipend equivalent to US$100 net per month.
• Annual stipend for conferences, courses, certifications, and continued learning.
• Sixteen weeks of paid parental leave after six months of employment.
• Equity for all full-time employees, comprehensive benefits including medical and retirement plans, paid holidays varying by country, and Docker swag.