Data Architecture Lead

We’re not just a company; we’re a global force, fiercely committed to ensuring that everyone, everywhere, can live their lives digitally safe. Our family of brands – Norton, Avast, LifeLock, Avira, AVG, ReputationDefender, and CCleaner – unites the brightest minds, the sharpest tech, and the most diverse thinking to protect over 500 million people. We’ve built an inclusive workplace where your well-being is a priority, because true success comes from balance and authenticity. If you’re ready to push boundaries and be part of something bigger, join #TeamGen.

How We Work
Our hybrid work style (50% at least working from the office) gives us the face-to-face time to have creative conversations, meaningful meetings, make quick decisions and build relationships. And it’s flexible enough to give you the space to do your best work.

We are seeking a highly specialized Data Architecture Lead to oversee and strategically advance our multi-petabyte data architecture, specifically for our subscription-based cybersecurity platform. This is a key leadership role responsible for managing a large team of 30+ engineers, architecting complex data migration projects, and implementing sophisticated analytics capabilities to drive business decisions in a high-volume, security-focused environment. 

Essential Qualifications (All Required) 

• Bachelor's degree in Computer Science, Data Engineering, or related technical field (Master's degree preferred) 

• Minimum 15 years of hands-on engineering experience specifically in large-scale data environments 

• Minimum 7 years of experience directly managing teams of data and software engineers, with proven track record of team growth and development 

• Extensive experience managing Snowflake platforms with > $1M /year annual spend. 

• Demonstrated experience successfully completing multiple enterprise-level migrations to Snowflake, including at least one documented migration specifically from Google BigQuery 

• Expert-level proficiency in SQL query optimization for multi-petabyte datasets 

• Advanced Python programming experience, specifically for data pipeline development and management 

• Demonstrated ability to build Kimball Warehouse architectures. 

• Verifiable experience building and scaling multiple engineering teams from the ground up 

• Extensive experience with AWS cloud infrastructure for large-scale data operations 

• Documented experience implementing and managing data solutions for subscription-based business models 

• Proven track record implementing cohort analysis frameworks, LTV calculations, marketing attribution frameworks and complex feature usage analytics systems  

• Hands-on experience with multi-petabyte data architectures, including partitioning strategies and performance optimization 

• Demonstrated expertise in CI/CD pipelines specifically for data engineering workflows 

• Proficiency in GitFflow and Trunk based development methodologies as applied to data engineering teams 

• Advanced implementation experience with either DBT or SQLMesh for data transformation workflows 

• Documented experience ensuring compliance with GDPR, PCI-DSS, HIPAA and other privacy/security requirements in data systems 

Specialized Experience Requirements 

• Must have direct industry experience in <