Senior Principal Data Engineer

About Gen

Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast, LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users in more than 150 countries.

Together, we share a collective passion and vision to protect consumers and help them grow, manage and secure their digital and financial lives. We’re always looking for smart, fearless and high-impact talent who see AI as a teammate – leveraging it to move faster and deliver meaningful results.

When you’re part of Gen, you’ll have the flexibility, tools and support to do your best work and grow your career – from flexible working options and time off to competitive pay, benefits and well-being programs.

At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.

If this sounds like you, we’d love you to be part of Gen.

About the Role

We are seeking an experienced Senior Principal Data Engineer to serve as a technical leader responsible for architecting systems within your team's domain and driving complex, cross-team projects that directly support our cybersecurity platform's strategic objectives. This role requires someone who can architect systems within your team's domain, reasonably be expected to come up with and drive the projects that your crew should do to solve complex business problems, and actively mentor other engineers.

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.