Gen Digital
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 Git flow 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 cybersecurity, ad-tech or another sector with demonstrable high-volume data processing [Billions per day]
Demonstrated success implementing data architectures supporting real-time analytics
Experience designing and implementing data models specifically for subscription-based businesses, including churn prediction, retention analysis, and lifetime value calculations
Must have built end-to-end data platforms supporting in-app engagement metrics and feature utilization analysis
Experience developing executive-level dashboards and analytics systems that directly inform product and business strategy
Previous success implementing data governance frameworks in regulated environments
Key Responsibilities
Direct and strategically lead a team of data engineers, data analysts, and data scientists
Own the architectural vision and implementation of our enterprise data platform
Lead multiple complex Snowflake migration initiatives, including strategy development, implementation planning, and execution
Design and implement sophisticated data pipelines supporting security analytics, customer behavior analysis, and financial reporting
Architect and oversee the implementation of advanced cohort analysis frameworks and feature usage tracking systems
Implement robust data governance and security controls, ensuring compliance with GDPR, PCI-DSS, and industry security standards
Develop and maintain a scalable data architecture capable of processing and analyzing multi-petabyte datasets
Collaborate with executive leadership to align data strategy with overall business objectives
Establish and enforce best practices for data engineering, including code reviews, documentation, and technical standards
Oversee the implementation and ongoing refinement of CI/CD pipelines for data workflows
Manage complex data transformations using enterprise tools like DBT or SQLMesh
Lead initiatives for data quality improvement and monitoring
Required Technical Skills
Advanced SQL optimization techniques for complex analytical queries
Python (including pandas, numpy, and data processing libraries)
Snowflake architecture and administration (advanced level)
AWS cloud services, particularly those related to data storage and processing
Data modeling for subscription-based business analytics
CI/CD implementation for data pipelines
Version control systems and gitflow workflows
Data transformation frameworks (dbt or SQLMesh)
Data security and privacy implementation techniques
Salary range: $200,000.00 - $270,000.00 The pay range depicts a base salary range for all positions except commission-based roles. The pay range for commission-based roles represents On Target Earnings (annual base salary + target annual commission). Additional compensation elements may be offered including an opportunity for bonus incentives and also competitive benefits package. Actual compensation offered will be determined by factors such as the external/internal market demand, location, level, job-related knowledge, skills, and experience. This position requires a unique combination of technical depth, leadership experience, and specialized domain knowledge. Due to the advanced nature of our data infrastructure and security requirements, candidates must meet all specified qualifications to be considered. Gen is proud to be an equal-opportunity employer, committed to diversity and inclusivity. We base employment decisions on merit, experience, and business needs, without considering race, color, national origin, age, religion, sex, pregnancy, genetic information, disability, medical condition, marital status, sexual orientation, gender identity or expression, military or veteran status, or other unlawful factors. Gen prohibits discrimination based on these protected characteristics and recruits talented candidates from diverse backgrounds. We consider individuals with arrest and conviction records and do not discriminate against employees for discussing their own pay or that of other employees or applicants.
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 Git flow 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 cybersecurity, ad-tech or another sector with demonstrable high-volume data processing [Billions per day]
Demonstrated success implementing data architectures supporting real-time analytics
Experience designing and implementing data models specifically for subscription-based businesses, including churn prediction, retention analysis, and lifetime value calculations
Must have built end-to-end data platforms supporting in-app engagement metrics and feature utilization analysis
Experience developing executive-level dashboards and analytics systems that directly inform product and business strategy
Previous success implementing data governance frameworks in regulated environments
Key Responsibilities
Direct and strategically lead a team of data engineers, data analysts, and data scientists
Own the architectural vision and implementation of our enterprise data platform
Lead multiple complex Snowflake migration initiatives, including strategy development, implementation planning, and execution
Design and implement sophisticated data pipelines supporting security analytics, customer behavior analysis, and financial reporting
Architect and oversee the implementation of advanced cohort analysis frameworks and feature usage tracking systems
Implement robust data governance and security controls, ensuring compliance with GDPR, PCI-DSS, and industry security standards
Develop and maintain a scalable data architecture capable of processing and analyzing multi-petabyte datasets
Collaborate with executive leadership to align data strategy with overall business objectives
Establish and enforce best practices for data engineering, including code reviews, documentation, and technical standards
Oversee the implementation and ongoing refinement of CI/CD pipelines for data workflows
Manage complex data transformations using enterprise tools like DBT or SQLMesh
Lead initiatives for data quality improvement and monitoring
Required Technical Skills
Advanced SQL optimization techniques for complex analytical queries
Python (including pandas, numpy, and data processing libraries)
Snowflake architecture and administration (advanced level)
AWS cloud services, particularly those related to data storage and processing
Data modeling for subscription-based business analytics
CI/CD implementation for data pipelines
Version control systems and gitflow workflows
Data transformation frameworks (dbt or SQLMesh)
Data security and privacy implementation techniques
Salary range: $200,000.00 - $270,000.00 The pay range depicts a base salary range for all positions except commission-based roles. The pay range for commission-based roles represents On Target Earnings (annual base salary + target annual commission). Additional compensation elements may be offered including an opportunity for bonus incentives and also competitive benefits package. Actual compensation offered will be determined by factors such as the external/internal market demand, location, level, job-related knowledge, skills, and experience. This position requires a unique combination of technical depth, leadership experience, and specialized domain knowledge. Due to the advanced nature of our data infrastructure and security requirements, candidates must meet all specified qualifications to be considered. Gen is proud to be an equal-opportunity employer, committed to diversity and inclusivity. We base employment decisions on merit, experience, and business needs, without considering race, color, national origin, age, religion, sex, pregnancy, genetic information, disability, medical condition, marital status, sexual orientation, gender identity or expression, military or veteran status, or other unlawful factors. Gen prohibits discrimination based on these protected characteristics and recruits talented candidates from diverse backgrounds. We consider individuals with arrest and conviction records and do not discriminate against employees for discussing their own pay or that of other employees or applicants.