Senior Manager, Data Engineering

We are seeking an experienced Senior Manager, Data Engineering to serve as a technical people leader responsible for owning the deliverables of your team and going the distance to empower them to achieve their objectives. You can expect to be architecting systems within your team's domain and driving complex, cross-team projects that directly support our cybersecurity platform's strategic objectives.

Responsibilities

Own the people management responsibilities of a team of driven Data Engineers – including performance & compensation management, hiring and mentorship; Extensive expertise operating & optimizing a modern data warehousing solution (Snowflake preferred) from both performance and cost perspectives; Expertise with Apache Kafka, real-time data processing, and event-driven architectures; Experience with Apache Iceberg, data lakehouse architectures, and modern table formats; Design and architect enterprise-scale data solutions that directly impact Gen's data strategy execution. Contribute a minimum of 1 exemplary technical spec per year that massively moves Gen’s data architecture forward; 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 and 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; Experience in planning day to day tasks, knowing how and what to prioritise and overseeing their execution; Experience working with PMO, other data specialities (analysts, scientists, machine learning), and working across time zones

Nice to have

Familiarity with AWS is a big plus

Benefits

flexible working options; time off; competitive pay; benefits; well-being programs