Note: The job is a remote job and is open to candidates in USA. Zscaler is an AI-forward enterprise that accelerates digital transformation for its customers. They are seeking a Senior Manager for the Enterprise Data Platform who will be responsible for driving the architecture, strategy, and evolution of their modern enterprise data platform, while preparing teams to become AI-ready.
Responsibilities
- Drive Platform Strategy, Architecture, & Evolution: Define the long-term technical roadmap, architecture, and strategy for the Enterprise Data Platform (utilizing Snowflake, dbt, Matillion DPC, and Streamlit). Balance the evolution toward modern platform operating models (medallion and mesh architectures) while actively supporting critical, high-impact, organization-wide business initiatives
- Enable Self-Service & Mesh Architectures: Empower decentralized business functions (such as Sales, Marketing, and Finance) to be entirely self-sufficient. Establish the fundamental analytics layers (Raw, Transform, Analytics) and deliver standard data contracts, allowing federated BI teams to easily build and run their own custom data models
- Embed AI into Data, Pipelines, & Analytics: Advance both the central and federated teams to become truly AI-ready. Design and implement strategies to embed AI directly into enterprise analytics, including building complex data pipelines (ETL), custom data apps, and Retrieval-Augmented Generation (RAG / Graph RAG) architectures directly on the data platform
- Architect AI-Driven Platform Operations & Governance: Implement frameworks for robust platform governance, data observability, and transparent cost attribution to optimize compute resources and Snowflake token consumption. You will be directly responsible for building and embedding automated AI systems (AIOps) to streamline platform operations—leveraging AI/LLMs for token cost optimization, automated metadata cataloging, and auto-triage of daily pipeline alerts
- Lead with Continuous Innovation & Hands-On Execution: Lead from the front as a hands-on manager who can jump into the codebase to tackle complex projects, prototype advanced workflows, or troubleshoot critical pipelines when required. Constantly research and evaluate the latest market trends and modern data technologies to keep our platform ecosystem at the cutting edge
Skills
- AI Readiness Strategy: Demonstrated experience driving technical strategies to transition traditional data structures and business intelligence teams into AI-ready units
- Proven Leadership: 5+ years of experience leading, mentoring, and growing high-performing data engineering, platform engineering, or analytics engineering teams
- Snowflake & dbt Expertise: Deep architectural and operational knowledge of Snowflake and dbt (analytics engineering, modeling standards, testing)
- Enterprise AI Infrastructure & Data Prep: Hands-on knowledge of designing data pipelines (ETL), analytics, and building/serving Retrieval-Augmented Generation (RAG) architectures—including Graph RAG—on cloud data platforms
- Self-Service & Mesh Experience: Practical experience implementing or operating within a self-service data platform environment and a Data Mesh architectural framework (Raw, Transform, Analytics)
- Modern ETL & Engineering Foundations: Strong hands-on experience with cloud-native ETL/ELT tools (preferably Matillion Data Productivity Cloud or similar) and strong software engineering skills in Python and SQL (CI/CD, Git, automated testing)
- Extreme Technical Depth: The ability to jump into the codebase, write complex code/models, and confidently lead the implementation of complex, highly technical data projects
- Advanced AI & Applications in Snowflake: Experience leveraging Snowflake's advanced AI capabilities (e.g., Cortex, Snowpark) and building custom data applications using Streamlit
Benefits
- Various health plans
- Time off plans for vacation and sick time
- Parental leave options
- Retirement options
- Education reimbursement
- In-office perks, and more!
Company Overview
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