Senior Manager, Data Engineering

About Zscaler Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise , we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate —we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession , collaboration, ownership, and accountability. We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. Role We are looking for a Senior Manager, Enterprise Data Platform to join our team. This is a remote (within the US) role, reporting to the Senior Director, Enterprise Data Platform in the IT Data Strategy department. In this role, you will be a key technical and strategic leader responsible for driving the architecture, strategy, and continuous evolution of our modern enterprise data platform.  You will lead the central data team, balancing its evolution into a highly effective, self-service platform team while actively supporting critical, high-impact, organization-wide data initiatives. A core focus of this role is preparing both the central data team and federated business intelligence units (such as Sales, Marketing, and other internal business functions) to become AI-ready, implementing strategies to embed AI directly into daily data analytics. This is a critical leadership position requiring a passionate innovator who is equally comfortable defining high-level strategy, establishing platform governance, and rolling up their sleeves to tackle complex, hands-on technical challenges. What you’ll do (Role Expectations) Drive platform strategy and architecture by defining the technical roadmap and long-term vision for the Enterprise Data Platform utilizing Snowflake, dbt, Matillion DPC, and Streamlit Balance platform evolution and business support, transitioning teams toward a modern platform operating model with medallion and mesh architectures while supporting critical organization-wide data initiatives Embed AI into data and analytics by designing pipelines, analytics models, and Retrieval-Augmented Generation systems to transition central data and federated BI teams into AI-ready units Enable self-service and mesh architecture to empower decentralized business functions to independently build custom data models across foundational analytics layers Implement robust platform governance, observability, and cost attribution frameworks while executing hands-on technical troubleshooting, prototyping advanced workflows, and developing AI/LLM-powered AIOps systems for operational efficiency Who You Are (Success Profile) Act as an owner with a strong bias for action, navigating seamlessly between defining high-level strategy and executing hands-on technical tasks. Approach complex data challenges as a natural problem-solver, energized by finding elegant solutions that deliver maximum business impact. Lead with deep integrity and accountability, building trust across the organization through transparent actions and high standards. Think at scale by connecting daily engineering initiatives to the global company mission and designing robust, future-proof data solutions. Foster high-trust collaboration by championing team success, participating in a healthy feedback culture, and driving cross-functional alignment. What We’re Looking for (Minimum Qualifications) Demonstrated experience driving technical strategies to transition data structures into AI-ready units, alongside hands-on knowledge of building Retrieval-Augmented Generation (RAG) and Graph RAG architectures Five or more years of experience leading, mentoring, and growing high-performing data engineering, platform engineering, or analytics engineering teams Deep architectural and operational knowledge of Snowflake and dbt, including analytics engineering, modeling standards, and testing Practical experience implementing or operating within a self-service data platform environment and a Data Mesh architectural framework Strong hands-on experience with cloud-native ETL/ELT tools, preferably Matillion Data Productivity Cloud or similar Solid software engineering foundations in Python and SQL, including CI/CD, Git, and automated testing What Will Make You Stand Out (Preferred Qualifications) Extreme technical depth with the ability to dive into codebases, write complex models, and lead highly technical data implementations Experience leveraging advanced Snowflake AI capabilities such as Cortex or Snowpark, and building custom data applications using Streamlit #LI-DY1 #LI-remote Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training. The base salary range listed for this f