Bhargav Mehta

I lead enterprise data. I build what makes it real.

Enterprise Data Architecture & Strategy Leader · 8+ years at BlackRock · Atlanta

One source of truth. Ready for AI.

I set the architecture, standards and roadmap that let a global firm trust its data, and I build alongside the teams that ship it.

20Data domains standardized
11AI use cases defined
1,000+Attributes unified
~50%Faster queries

As a leader

Leadership

  1. 01

    Enterprise Semantic Data Platform

    One governed source of truth for global investment data.

    Aladdin Data Cloud · BlackRock

    • Four-tier standard across 20 domains, retiring legacy ETL.
    • Used globally by PMs, traders, risk and executives.

    2026In 2026, expanded the governed semantic consumption layer across seven core investment-data domains: Trade, Position, Security, Orders, Price, Cashflow and Cash, with client-specific extensibility (custom UDF automation) and governance and discoverability built in.

    Semantic coverage, 2026
    Trades Positions Risk Reference Market data Accounting Semantic layer 4 tiers BI APIs AI 20 domains · 1,000+ attributes
  2. 02

    From Semantic Layer to BI & Analytics

    Now leading the BI strategy for Aladdin Data Cloud.

    Aladdin Data Cloud · BlackRock · 2026

    Turning the semantic foundation into client-facing analytics: a unified embedded-analytics program spanning authentication, governance, embedded analytics and migration, and modernizing legacy BusinessObjects reporting onto the new platform.

    The goal is measurable outcomes: more clients self-serving reports, lower cost of custom reporting, and legacy platforms retired.

    Semantic layer BusinessObjects BI program Authentication Governance Embedded analytics Migration Self-service Lower cost Legacy retired
  3. 03

    AI Strategy & Roadmap

    11 AI bets, ranked by value, from anticipatory analytics to autonomy.

    The semantic layer is becoming the governed business meaning and relationships that Aladdin's AI experiences rely on, evolving from a reporting abstraction into AI-ready data architecture.

    Foundation Pilot Scale 01 02 03 04 05 06 07 08 09 10 11 Anticipatory analytics Autonomy
  4. 04

    Shaping Vendor Roadmaps

    Design partner to Denodo and Snowflake product leadership.

    Enterprise requirements Feedback Denodo Product roadmap Snowflake Product roadmap
  5. 05

    Governance at Scale

    Trust built in: quality, reconciliation and SLA observability across IBOR and Risk.

    IBOR Risk Reconcile Quality SLA Policy Query time Before After ~50% faster queries

As a builder

Builds

  1. 01

    Cited RAG Knowledge Platforms

    AI answers you can verify, sentence by sentence.

    Independent build · hybrid search, reranking, citation verification

    Query Ask a question Doc 1 Doc 2 Doc 3 Answer [1] [2] [3]
  2. 02

    AI Root-Cause Engine

    Azure OpenAI that diagnoses data discrepancies and scores its own confidence.

    BlackRock

    Threshold Anomaly Root cause Confidence scored Ruled out Ruled out
  3. 03

    Automated Data Pipeline

    A self-hosted pipeline that enriches and categorizes data nightly, unattended.

    Independent build

    Nightly · unattended Ingest Validate Transform Publish

Approach

How data becomes value

  1. 01

    Source data

    Trade, position, security, price and cash data from many systems.

  2. 02

    Semantic layer

    One governed model with business meaning, definitions and lineage.

  3. 03

    Report-ready data

    Reusable, analysis-ready datasets clients can trust.

  4. 04

    Self-service BI

    Clients build their own reports in Power BI, Tableau and embedded analytics.

  5. 05

    AI experiences

    AI that understands what the data means, not just where it lives.

Bio

Architect. Strategist. Builder.

Since 2018, Bhargav has led enterprise data architecture at BlackRock's Aladdin Data Cloud, owning the semantic data platform strategy from trade to risk on Snowflake and Denodo. He owns a critical part of the consumption strategy for Aladdin Data Cloud: in 2026 he built out the governed semantic foundation, and his focus now is converting it into adoption, retention and operating leverage through BI and AI.

He advises vendor product leadership, leads architecture reviews and standards, and mentors early-career engineers. He stays hands-on with AI so his strategy is grounded in what works.

Focus areas

  • Enterprise Data Architecture
  • Data Strategy
  • Semantic & Metrics Layers
  • Business Intelligence & Embedded Analytics
  • Data Governance
  • Data Products
  • Lakehouse & Data Mesh
  • AI-Ready Data
  • Investment Data (IBOR/ABOR)
  • Vendor Partnerships
  • Team Leadership

Education

M.S. Computer & Information Sciences, New Jersey Institute of Technology · B.E. Information Technology, Ahmedabad Institute of Technology

Keep up

Let's build what's next.