Senior Manager, Data Engineering (West Coast Preferred)

Docker, Inc. is a leading company in app development, seeking a Senior Manager to lead their Data Engineering team. This role involves driving the strategic evolution of data analytics, building scalable data infrastructure, and enabling data-driven decision making across various teams.

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 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

Requirements:

• 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 ability to influence executives and technical teams
• 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)
• Knowledge of infrastructure-as-code practices and modern DevOps tools
• Understanding of SaaS business models, product analytics, and customer lifecycle metrics
• Experience with customer-facing analytics and embedded reporting capabilities
• Knowledge of data privacy regulations, security frameworks, and enterprise compliance requirements
• Familiarity with developer tools and infrastructure software business models
• Experience supporting product launches with data infrastructure and analytics capabilities
• 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 technical 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