4 hours ago
Base Salary
$161k - $261k/yr
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.
Tech Stack
Categories
Data Engineering
About Docker
Docker builds developer tools for building, sharing, and running containerized applications, including Docker Desktop, Docker Hub, Docker Scout, and the open-source Docker Engine. It monetizes through paid subscriptions for individuals, teams, and enterprises, along with security offerings such as Docker Hardened Images. Founded in 2013 and headquartered in San Francisco, the company serves over 20 million monthly users and supports more than 20 billion container image pulls.