Senior Manager, Data Engineering

You'll serve as a technical people leader responsible for owning your team's deliverables and empowering them to achieve their goals. You'll architect systems within your team's domain and drive complex, cross-team projects that support the company's cybersecurity platform strategy. You'll split your time between hands-on coding, PR reviewing, and managing your team across its full domain. You'll participate in and improve the hiring process and act as a champion of the org's cross-geographical RFC and technical specification review process. You'll craft thoughtful solutions that empower everyone at the company toward an agentic AI-first analytics and development lifecycle.

Responsibilities

• Own the people management responsibilities of a team of Data Engineers, including performance and compensation management, hiring and mentorship
• Operate and optimize a modern data warehousing solution from performance and cost perspectives
• Apply expertise with Apache Kafka, real-time data processing, and event-driven architectures
• Apply experience with Apache Iceberg, data lakehouse architectures, and modern table formats
• Design and architect enterprise-scale data solutions that impact data strategy execution
• Contribute at least one exemplary technical spec per year advancing the data architecture
• Lead evaluation and implementation of cutting-edge technologies including modern data stack and advanced analytics
• Collaborate with executives and senior leadership to align data architecture with business strategy
• Manage senior stakeholders from external departments
• Drive complex, multi-quarter technical initiatives requiring coordination across multiple engineering teams

Requirements

• Bachelor's degree in computer science, Data Engineering, or related technical field
• 5-10 years of hands-on data engineering experience in large-scale, high-volume environments, with 1-2 years of management experience
• Expert-level proficiency in SQL optimization for multi-petabyte datasets and advanced Python programming
• Extensive experience with Snowflake architecture, optimization, and cost management at enterprise scale
• Demonstrated expertise building Kimball dimensional data warehouses and star schema architectures
• Advanced experience with AWS cloud infrastructure and either DBT or SQLMesh for data transformations
• Hands-on experience with CI/CD pipelines, GitFlow, and data governance frameworks ensuring GDPR/PCI-DSS compliance
• Familiarity with AWS is a big plus
• Experience planning day to day tasks, prioritizing, and overseeing execution
• Experience working with PMO, other data specialities (analysts, scientists, machine learning), and working across time zones