Staff Data Engineer [Remote]

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.

We are seeking an exceptional Staff Data Engineer to join our team as a senior technical leader responsible for architecting and implementing enterprise-scale data solutions that directly impact our cybersecurity platform's strategic objectives. This role combines deep technical expertise with significant organizational influence, requiring someone who can design complex data architectures, mentor engineering teams, and drive the technical vision for our multi-petabyte data infrastructure serving millions of users.

• Expertise with Apache Kafka, real-time data processing, and event-driven architectures
• Experience with Apache Iceberg, data lakehouse architectures, and modern table formats
• Demonstrated expertise in cloud cost optimization and data warehouse performance tuning
• Design and architect enterprise-scale data solutions that directly impact Gen's data strategy execution. This might be something like designing and implementing an incremental identity graph, integrating a marketing attribution vendor or automating LTV calculation.
• 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
• Mentor IC9 and IC10 engineers, focusing on architectural decision-making and advanced technical skills
• Drive complex, multi-quarter technical initiatives requiring coordination across multiple engineering teams

• Bachelor's degree in computer science, Data Engineering, or related technical field (master's degree preferred)
• Minimum 10-15 years of hands-on data engineering experience in large-scale, high-volume environments
• 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
• Proven ability to architect and own multiple entire areas of the codebase or services independently
• Experience with MLOps frameworks, LLM integration, vector databases, and AI-driven analytics. We know its new, but some familiarity is a plus.
• Proven track record with subscription business models including cohort analysis, LTV calculations, and marketing attribution
• Direct industry experience in cybersecurity, ad-tech, or high-volume data processing environments (billions of events per day)
• This position requires a unique combination of deep technical expertise, strategic thinking, and leadership capabilities. The successful candidate will be a recognized expert in their domains within the broader data engineering community and capable of driving significant technical and business impact at enterprise scale.

• TA Call
• Technical Screening Focused on Python and SQL
• Technical Screening Focused on Snowflake and dbt
• Final Interview - Whiteboarding Design Round