Docker needs a visionary technical leader to build world-class data infrastructure and establish analytics capabilities that power product innovation, business intelligence, and customer insights as the company expands its product portfolio and serves millions of developers and thousands of enterprise customers globally.
Requirements
- Deep hands-on experience with Snowflake including data warehousing, performance optimization, and cost management
- Proficiency with Apache Airflow for orchestrating complex data workflows and pipeline management
- Strong expertise in DBT (Data Build Tool) for data transformation, modeling, and testing
- Extensive AWS experience including data services (S3, Redshift, EMR, Glue, Lambda) and infrastructure management
- Experience with Sigma or similar modern BI platforms for self-service analytics and data visualization
- Strong background in data pipeline development, ETL/ELT processes, and streaming data architectures
- Proficiency with programming languages commonly used in data engineering (Python, SQL, Scala)
Responsibilities
- Architect and oversee development of scalable, reliable data infrastructure leveraging Snowflake as the core data warehouse and AWS cloud services
- Drive implementation of modern data orchestration using Airflow for workflow management and DBT for data transformation and modeling
- Lead technical decisions around data platform technologies, vendor selection, and build vs. buy strategies
- Establish data governance, security, and compliance frameworks to support enterprise customer requirements
- Oversee modernization of legacy data systems and migration to cloud-native data platforms
- Establish self-service analytics capabilities using Sigma and other BI tools enabling teams across Docker to access and analyze data independently
- Build comprehensive dashboards and reporting systems for product metrics, business KPIs, and operational insights
Other
- Build, lead, and scale a high-performing data engineering team of 8-12 engineers across data infrastructure, analytics, and business intelligence
- Establish hiring standards and recruit top-tier data engineering talent in a competitive market
- Foster a culture of technical excellence, innovation, and customer obsession within the data organization
- Mentor senior engineers and develop next-generation technical leadership within the data discipline
- Partner with HR and Engineering leadership on career development, performance management, and team growth
