Enterprise AI, cloud & data

Experience

I build enterprise platforms that help teams turn data and AI into useful products. My 20 years in financial services span hands-on data work, product strategy, and leadership of cross-functional teams.

Portrait of Ganesh Iyer
Ganesh Iyer

  1. 2021 – Present

    New York

    Principal Product Manager

    American Express

    NextGen Cloud · Enterprise data & ML platform

    Owned developer-facing platform strategy for a governed GCP platform supporting 15,000+ analytical users, 350+ applications, and approximately 30 PB of data.

    • AI-powered migration. Launched GenAI-assisted PySpark-to-BigQuery code conversion, reducing migration effort by 60%.

    • Self-service cloud access. Owned self-service, on-demand notebook and Vertex AI Workbench provisioning through APIs and Terraform orchestration, with quotas and workload isolation for scale. Lumi Portal served 3,000+ notebook users within a cloud migration serving 10,000+ users.

    • Platform reliability & governance. Defined API contracts, product requirements, and roadmaps, including workload isolation, recovery, access controls, auditability, and cost controls.

    • AI agent exploration. Prototyped MCP and agent-oriented architecture for governed access to enterprise data and analytics; this work focused on proofs of concept.

  2. 2016 – 2020

    New York

    Senior Product Manager

    American Express

    Cornerstone · Enterprise data lake

    Defined product strategy and reusable ingestion, curation, and delivery patterns for a data platform powering 500+ use cases across 12+ lines of business.

    • Data quality from 0 to 1. Created Calibrate, an enterprise self-service data quality product adopted by 3,500+ users and processing 600,000+ checks daily.

    • Reusable data products. Built unified ingestion and metadata capabilities across 900+ tables and 100,000+ attributes, with governed discovery and access workflows.

    • ML-powered data management. Applied NLP to metadata enrichment and lineage, improving attribute accuracy by 10% across 500,000+ fields and reducing curation from weeks to hours.

    • Team leadership. Grew and mentored a 50+ person organization spanning product, engineering, data, and machine learning.

  3. 2010 – 2015

    New York

    Product Owner

    Credit Suisse

    Reference & master data platforms · Legal Netting Library

    Owned platform strategy and delivery for reference data and legal netting capabilities supporting back-office operations, regulatory processes, and enterprise data distribution.

    • Delivery leadership. Led 20 engineers and analysts to 100% on-time delivery for critical sourcing and distribution initiatives while managing 10 complex platform programs.

    • Data integration. Integrated 50+ data sources, reducing manual data handling by 30%.

    • Trusted enterprise data. Established interface specifications, service-level agreements, sensitive-data classifications, audit controls, and master data stewardship workflows.

  4. 2006 – 2009

    New York

    Business / Data Analyst

    Startups & Financial Services

    Data warehouses, data marts & business intelligence

    Built data and business intelligence solutions for mortgage and financial-services organizations, including Freddie Mac.

    • Mortgage analytics. Built data products supporting loan performance, risk assessment, portfolio management, and regulatory reporting.

    • Data consistency & access. Partnered with data stewards to document business rules, validate definitions, and establish access controls for sensitive borrower and financial data.