Manager, Analytics & Agentic Platform OperationsTink • San Francisco, California, United States
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Manager, Analytics & Agentic Platform Operations
Tink
- San Francisco, California, United States
- San Francisco, California, United States
À propos
Responsibilities
Security & Access Control (Execution): 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.
Agent Orchestration & AI-Driven Infrastructure: 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.
Data Pipeline Development (Fabric): 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.
Platform Administration: 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.
Infrastructure as Code (CI/CD): 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.
FinOps & Cost Monitoring: 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.
Data Observability: 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.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Basic Qualifications
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
Preferred Qualifications
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.
Salary and Benefits Estimated salary range: $169,100 to $270,800 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job‑related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.
U.S. Applicants Only.
Work Hours Varies upon the needs of the department.
Travel Requirements This position requires travel 5‑10% of the time.
Mental/Physical Requirements This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
EEO Statement Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law, including the requirements of Article 49 of the San Francisco Police Code.
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Compétences linguistiques
- English
Avis aux utilisateurs
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