Senior Manager, Data Engineering
Skills
Data LakehouseReal-Time Data ProcessingSql OptimizationApache KafkaSqlmeshSnowflakeDbtPeople ManagementGdprEvent-Driven ArchitectureAwsCi/CdData EngineeringGitMentorshipPythonStakeholder ManagementKimball Dimensional ModelingGitflowPci DssHiringData GovernanceDimensional ModelingTechnical SpecificationApache IcebergStar Schema
About the Role
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.
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
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
