Senior Manager, Enterprise Data Platform

Zscaler

1d•$196,000 - $245,000•Remote

About The Position

Zscaler is seeking a Senior Manager, Enterprise Data Platform to join their IT Data Strategy department. This remote role (within the US) will be a key technical and strategic leader responsible for the architecture, strategy, and evolution of the company's modern enterprise data platform. The position involves leading the central data team, transforming it into a self-service platform, and supporting organization-wide data initiatives. A primary focus is preparing the data team and federated business intelligence units for AI readiness by embedding AI into daily data analytics. This leadership role requires a blend of strategic thinking, platform governance, and hands-on technical problem-solving.

Requirements

Demonstrated experience driving technical strategies to transition traditional data structures and business intelligence teams into AI-ready units.
5+ 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 (analytics engineering, modeling standards, testing).
Hands-on knowledge of designing data pipelines (ETL), analytics, and building/serving Retrieval-Augmented Generation (RAG) architectures—including Graph RAG—on cloud data platforms.
Practical experience implementing or operating within a self-service data platform environment and a Data Mesh architectural framework (Raw, Transform, Analytics).
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).

Nice To Haves

The ability to jump into the codebase, write complex code/models, and confidently lead the implementation of complex, highly technical data projects.
Experience leveraging Snowflake’s advanced AI capabilities (e.g., Cortex, Snowpark) and building custom data applications using Streamlit.

Responsibilities

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.
Empower decentralized business functions (Sales, Marketing, Finance) to be self-sufficient by establishing fundamental analytics layers (Raw, Transform, Analytics) and delivering standard data contracts.
Advance both central and federated teams to become AI-ready by designing and implementing 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.
Implement frameworks for robust platform governance, data observability, and transparent cost attribution to optimize compute resources and Snowflake token consumption.
Build and embed 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 from the front as a hands-on manager, capable of tackling complex projects, prototyping advanced workflows, or troubleshooting critical pipelines.
Constantly research and evaluate the latest market trends and modern data technologies to keep the platform ecosystem at the cutting edge.