As a Senior Principal Data Engineer, you will fully understand and own multiple entire areas of the codebase or multiple services, work with your Manager or a Technical Director to validate your technical decisions when you ask for input, and contribute significantly to our data engineering practices and standards.
Key Responsibilities
Cross-Team Projects: Lead projects that cross teams, actively working with your Manager to set the technical vision for your team
Problem Solving: Be handed a problem and reasonably be expected to come up with and drive the projects that your crew should do to solve that problem
System Architecture: Architect systems that are within your team's domain, with guidance from Manager or Technical Director when needed
Domain Ownership: Fully understand and own multiple entire areas of the codebase or multiple services
Technology Integration: Lead evaluation and implementation of new technologies that benefit your team's domain
Quality Standards: Ensure all work meets our high-quality pull request standards and follows established engineering processes
Cross-Functional Collaboration: Collaborate across teams inside the Data Engineering org, represent your team as needed, and reach out to external stakeholders for clarifications
Mentoring: Actively mentor IC7s and IC8s, focusing on adopting our processes, technical knowledge, and quality of execution
Stakeholder Engagement: Work with engineers in the rest of Gen to help move the org forward
Technical Output: Minimum 4+ PRs per week (GitFlow) or 6+ PRs per week (Trunk-based development)
Code Reviews: 2+ comprehensive reviews per day from anyone in the areas/services you contribute to
Documentation: Author at least 1+ RFC or Tech Spec per year that demonstrates technical leadership
Meeting Efficiency: No more than 15% of work hours spent in meetings to maintain focus on technical work
Deployments: Routinely deploy to production with appropriate oversight and process adherence
Domain Knowledge: Extremely knowledgeable in your domains and able to almost always help anyone coming to you with technical questions
Development Skills: Expert in at least one of SQL and Python, with strong understanding of the other enough to be an effective IC10
Process Excellence: Very reliably follow our processes with code that only requires revisions for architectural reasons
Architecture Understanding: Contribute to the architecture of systems within your team's domain
Collaboration: Collaborate across teams inside the Data Engineering org and represent your team to external stakeholders when needed
About You
Bachelor's degree in computer science, Data Engineering, or related technical field (master's degree preferred)
Minimum 6-10 years of hands-on data engineering experience in large-scale, high-volume environments
Expert proficiency in at least one of SQL and Python, with strong understanding of the other
Extensive experience with Snowflake architecture, optimization, and performance tuning
Demonstrated experience building Kimball dimensional data warehouses and star schema architectures
Strong AWS cloud infrastructure experience with focus on data operations
Production experience with either DBT or SQL Mesh for data transformation workflows
Experience with CI/CD pipelines, GitFlow/trunk-based development, and data governance frameworks
Knowledge of compliance requirements (GDPR, PCI-DSS) in data systems
Proven ability to architect systems that are within your team's domain on your own
Streaming & Real-time Processing: Experience with Apache Kafka, event-driven architectures, and real-time analytics pipelines
Modern Data Architecture: Familiarity with Apache Iceberg, data Lakehouse architectures, and modern table formats
Performance Optimization: Experience with data warehouse performance tuning and cost optimization practices
Subscription Business Models: Experience with cohort analysis, LTV calculations, churn prediction, or marketing attribution frameworks
High-Volume Industries: Experience in cybersecurity, ad-tech, fintech, or similar industries processing large volumes of data
Complex Analytics: Experience building feature usage analytics, behavioral analysis, or executive reporting systems
This position is ideal for an experienced data engineering professional who wants to take on significant technical leadership responsibilities, enjoys mentoring others, and thrives on solving complex data challenges in a high-growth cybersecurity environment.
What's Next
TA Screening Call
Technical Screening Focused on Python and SQL
Technical Screening Focused on Snowflake and Dimensional Modeling
Final Interview - Whiteboarding Design Round
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Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.
