Manager, Analytics & Agentic Platform Operations

Visa•Foster City, CA

12d•$169,100 - $270,800•Hybrid

About The Position

We are seeking a Manager of Analytics & Agentic Platform Operations to build and run our data platform end-to-end. You will be the hands-on owner of our Microsoft Fabric and Azure environment—not only ensuring the “health of the pipes” (stability, security, cost, and automation), but actively building the pipes: designing data pipelines within Fabric and developing the agentic AI solutions that run on top of them. Critically, you are an agent orchestrator—leveraging AI to build out the infrastructure itself, directing agents that execute on loops and standing up automated frameworks that continuously flag inconsistencies across the environment. You are equal parts platform operator and builder, acting as the bridge between high-level architecture and daily execution while pushing the platform toward an AI-first, self-operating future.

Requirements

5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
6 or more years of work experience with a Bachelors Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD
5+ years of experience in Data Engineering, DevOps, or Database Administration, with hands-on data pipeline development.
Highly proficient in data and dimensional modeling and distributed systems —particularly PySpark and Hadoop.
Demonstrated experience building and orchestrating data pipelines in Microsoft Fabric (Data Factory pipelines, notebooks, Lakehouse) and/or the Azure Data Stack (Synapse, Data Factory, SQL Database).
Source-system ingestion: to ingest and pipe data into Fabric, working knowledge of Hadoop, Bash/Shell scripting and SSH, Trino and Hive SQL, and familiarity with Airflow.
Ability to script in SQL and Python/PowerShell for automation tasks.
Proven ability to orchestrate AI agents —designing multi-step agentic workflows, running agents on automated loops, and building frameworks that validate infrastructure and flag inconsistencies.
Hands-on experience with LLM-powered agents, MCP servers, and an AI-first approach to building and operating platforms.
Hands-on experience leveraging agentic CLI coding tools such as Claude Code, Codex, or a comparable command-line agent to build, automate, and operate infrastructure.
Familiarity with LLMOps/MLOps observability platforms (e.g., LangSmith or comparable) to monitor, trace, and evaluate agent and model behavior.
Demonstrated experience implementing complex security models (RLS, OLS, CLS) in a regulated environment.
Hands-on experience with GitHub Actions and CI/CD for data platforms.
Self-sufficient navigator —able to quickly triage and unblock independently by trawling Confluence/wikis and building connections across Visa to track down resources, permissions, and system access.
As a senior individual contributor, comfortable operating across a variety of unfamiliar technical systems with minimal hand-holding.
U.S. Applicants Only

Responsibilities

Implement and maintain granular security protocols to protect sensitive data. This includes writing and managing scripts for Row Level Security (RLS), Column Level Security (CLS), and Object Level Security (OLS) to ensure strict data isolation and PII protection across the platform.
Act as an agent orchestrator—leveraging AI to build out and maintain the platform itself. Design and run AI agents on automated loops, and develop self-running frameworks that continuously validate the environment and flag inconsistencies (security drift, schema changes, broken lineage) before they become problems. Build and operationalize MCP servers, automation agents, and copilots that enable natural-language data access and self-healing pipelines.
Design, build, and orchestrate data pipelines and Spark/PySpark notebooks within Microsoft Fabric—ingesting, transforming, and moving data across the Bronze/Silver/Gold medallion architecture to deliver reliable, production-grade datasets.
Manage the daily operations of Microsoft Fabric Capacities and Azure resources. Monitor system health, troubleshoot failed pipelines, and resolve connectivity issues for the analytics team.
Maintain GitHub Action workflows to ensure database changes, pipeline deployments, and infrastructure updates are deployed smoothly across Dev, Test, and Prod environments with minimal manual intervention.
Take direct ownership of cloud and AI spend. Track daily consumption against budgets, identify “runaway” queries and inefficient agent/LLM token usage, and optimize capacity, model, and query settings to prevent billing overages.
Implement monitoring alerts (using SQL or third-party tools) to detect “silent” data failures—such as stale data, schema drift, or volume anomalies—before they impact business users. Extend the same rigor to AI workloads—monitoring agent and model behavior for drift, errors, and runaway loops.