Senior Manager, Data Engineering

Senior Manager, Data Engineering Base pay range: $231,600.00/yr - $318,450.00/yr At Docker, we make app development easier so developers can focus on what matters. Our remote‑first team spans the globe, united by a passion for innovation and great developer experiences. With over 20 million monthly users and 20 billion image pulls, Docker is the #1 tool for building, sharing, and running apps—trusted by startups and Fortune 100s alike. We’re growing fast and just getting started. Come join us for a whale of a ride Docker is seeking a Senior Manager to lead our Data Engineering team and drive the strategic evolution of data analytics across the company. The role combines technical leadership with people management to build a high‑performing data engineering organization. Responsibilities include shaping Docker’s data strategy, establishing scalable data pipelines and platforms, and enabling data‑driven decision making across Product, Engineering, Sales, Marketing, and Executive teams. Key Responsibilities 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. Partner with HR and Engineering leadership on career development, performance management, and team growth. Define and execute the long‑term technical strategy for Docker’s data platform, ensuring alignment with business objectives. 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 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 to enable 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 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. 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. Required Qualifications 8+ years of data engineering experience with 4+ years in technical leadership roles managing teams of 5+ engineers. Proven track record building and scaling data engineering organizations at high‑growth technology companies. Strong people management skills including hiring, performance management, and career development. Experience leading cross‑functional initiatives involving Product, Engineering, and Business stakeholders. Excellent communication skills with the ability to influence executives and technical teams. Deep hands‑on experience with Snowflake, Apache Airflow, DBT, AWS data services, and BI platforms such as Sigma. Strong expertise in programming languages commonly used in data engineering (Python, SQL, Scala). Knowledge of data privacy regulations, security frameworks, and enterprise compliance requirements. Understanding of SaaS business models, product analytics, and customer lifecycle metrics. Preferred Qualifications Experience at developer tools, infrastructure software, or container technology companies. Background in platform engineering or developer experience roles. Experience with machine learning platforms and MLOps practices using AWS SageMaker or similar. Knowledge of container technologies, Kubernetes, or cloud‑native development. Advanced degree in Computer Science, Data Science, or related field. Experience with real‑time analytics and event‑driven architectures. Familiarity with modern data catalog tools and metadata management. Experience with additional cloud data warehouses (BigQuery, Databricks) for multi‑cloud strategies. Key Success Metrics Team performance and retention rates with strong employee satisfaction scores. Successful delivery of data platform capabilities enabling new product features and business initiatives. Improved data accessibility and self‑service adoption across Docker teams. Customer satisfaction scores for data and analytics solutions. Cost optimization and operational efficiency improvements for Snowflake, AWS, and infrastructure. Data quality and reliability metrics meeting enterprise SLA requirements. Successful implementation and adoption of modern data stack (Snowflake + Airflow + DBT + Sigma). Perks Freedom & flexibility; fit your work around your life. Designated quarterly Whaleness Days. Home office setup. 16 weeks of paid parental leave. Technology stipend equivalent to $100 net/month. PTO plan that encourages time off. Quarterly, company‑wide hackathons. Training stipend for conferences, courses and classes. Equity. Docker Swag. Medical benefits, retirement and holidays vary by country. Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be. Due to the remote nature of this role, we are unable to provide visa sponsorship. #J-18808-Ljbffr