• 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 • Ensure team participation in the on-call rotation and step in as needed. Respond to incidents, troubleshoot production issues, and drive continuous improvement in system reliability. • Define and execute the long-term technical strategy for Docker's data platform, ensuring alignment with business objectives and product roadmap • 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 • Partner with Product Management teams to enable data-driven product development and feature validation • Collaborate with Sales and Customer Success teams to deliver customer-facing analytics and reporting capabilities • Support Marketing and Growth teams with user behavior analytics, funnel optimization, and campaign effectiveness measurement • Work with Finance team to enable accurate business reporting, forecasting, and operational metrics • Engage directly with enterprise customers to understand analytics requirements and deliver custom data solutions • 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 • Implement advanced analytics capabilities including machine learning, predictive modeling, and anomaly detection • Drive adoption of data visualization tools and establish best practices for analytics across the organization • Lead data literacy initiatives and training programs to increase analytical capabilities company-wide • Own the operational excellence of Docker's data platform including Snowflake performance optimization, Airflow pipeline reliability, and AWS cost management • Establish comprehensive monitoring, alerting, and incident response procedures for data systems across the modern data stack • Implement robust data quality frameworks and automated testing for DBT models, data pipelines, and analytics • Drive cost optimization initiatives for Snowflake compute, AWS infrastructure, and analytics tools • Ensure compliance with data privacy regulations (GDPR, CCPA) and enterprise security requirements