Senior Data Analyst (10-12 yrs)
Who Are We :
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 - unite the brightest minds, the sharpest tech and the most diverse thinking to protect over 500 million people. And we've built an inclusive workplace, where your well-being is a priority because true success comes from a place of balance and authenticity. When you're thriving, you're unstoppable. So, bring us your bold ideas and passion that refuses to quit. The digital world isn't some distant reality - it's the world we live in, and we're ready for it. If you're ready to push boundaries and be part of something bigger, join #TeamGen.
How We Work :
We are a thriving, globally distributed team focused on building innovative mobile app solutions in security, utilities, and finance. Leveraging modern technologies, including AI-powered tools, we experiment, evaluate, and drive impactful change, creating secure, high-performance products across the globe.
Mission and Goals :
- We are seeking an experienced Senior Data Analyst 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 Data Analyst , 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 Leadership & Project Ownership :
- 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
Implementation & Development :
Domain Ownership : Fully understand and own multiple entire areas of the codebase or multiple servicesTechnology Integration : Lead evaluation and implementation of new technologies that benefit your team's domainQuality Standards : Ensure all work meets our high-quality pull request standards and follows established engineering processesCollaboration & Mentoring :
Cross-Functional Collaboration : Collaborate across teams inside the Data Engineering org, represent your team as needed, and reach out to external stakeholders for clarificationsMentoring : Actively mentor IC7s and IC8s, focusing on adopting our processes, technical knowledge, and quality of executionStakeholder Engagement : Work with engineers in the rest of Gen to help move the org forwardQuantifiable Performance Expectations :
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 toDocumentation : Author at least 1+ RFC or Tech Spec per year that demonstrates technical leadershipMeeting Efficiency : No more than 15% of work hours spent in meetings to maintain focus on technical workDeployments : Routinely deploy to production with appropriate oversight and process adherenceTechnical Competency Expectations :
Domain Knowledge : Extremely knowledgeable in your domains and able to almost always help anyone coming to you with technical questionsDevelopment Skills : Expert in at least one of SQL and Python, with strong understanding of the other enough to be an effective IC10Process Excellence : Very reliably follow our processes with code that only requires revisions for architectural reasonsArchitecture Understanding : Contribute to the architecture of systems within your team's domainCollaboration : Collaborate across teams inside the Data Engineering org and represent your team to external stakeholders when neededCareer Impact & Growth :
This role represents a senior individual contributor position within our Data Engineering organization where you'll have the opportunity to :Lead Technical Projects : Drive complex, cross-team initiatives that solve important business problemsMentor Junior Engineers : Help develop the next generation of data engineering talent through active mentoringShape Team Standards : Contribute to establishing and maintaining high engineering standards within your domainSolve Complex Problems : Work on challenging technical problems that require deep expertise and creative solutionsCollaborate Across Teams : Build relationships and work effectively with stakeholders across the Data Engineering 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 environmentsExpert proficiency in at least one of SQL and Python, with strong understanding of the otherExtensive experience with Snowflake architecture, optimization, and performance tuningDemonstrated experience building Kimball dimensional data warehouses and star schema architecturesStrong AWS cloud infrastructure experience with focus on data operationsProduction experience with either DBT or SQL Mesh for data transformation workflowsExperience with CI / CD pipelines, GitFlow / trunk-based development, and data governance frameworksKnowledge of compliance requirements (GDPR, PCI-DSS) in data systemsProven ability to architect systems that are within your team's domain on your ownAdvanced Technical Requirements :
Streaming & Real-time Processing : Experience with Apache Kafka, event-driven architectures, and real-time analytics pipelinesModern Data Architecture : Familiarity with Apache Iceberg, data Lakehouse architectures, and modern table formatsPerformance Optimization : Experience with data warehouse performance tuning and cost optimization practicesDomain Expertise (Preferred) :
Subscription Business Models : Experience with cohort analysis, LTV calculations, churn prediction, or marketing attribution frameworksHigh-Volume Industries : Experience in cybersecurity, ad-tech, fintech, or similar industries processing large volumes of dataComplex Analytics : Experience building feature usage analytics, behavioral analysis, or executive reporting systemsThis 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.(ref : iimjobs.com)