Enterprise Data Architect · MBA

Turning fragmented data into trusted foundations for analytics and AI.

I help organizations modernize complex data environments, align enterprise data models, and build cloud data platforms on Databricks, Snowflake and Azure. Twenty years of it, across healthcare, insurance, pharma, utilities and manufacturing.

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New York City Metro · open to US remote roles and advisory work

DATA ARCHITECT · 20+ YEARS

20+ yrsin data architecture, warehousing and BI

10organizations, from KPMG to GEHA

6industries, led by healthcare and insurance

Who I work with

Two ways to work together.

For hiring teams

A senior architect who designs the model and builds the platform.

Principal and Enterprise Data Architect roles
Healthcare and insurance data architecture
Cloud data platform and lakehouse architecture
Data architecture lead for delivery teams

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For organizations

Independent advice on where your data platform should go next.

Warehouse-to-lakehouse modernization plans
Enterprise and common data models across systems
Governance, MDM and data quality foundations
Getting your data ready for AI

Data Architecture Health Check A current-state architecture diagram, a prioritized list of risks, and a 90-day roadmap.

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From over an hour to under three minutes.

KPMG's eDataMining product reported audit performance in near real time, but each client engagement took more than an hour to process. I redesigned the solution architecture with parallel ETL, table partitioning, rebuilt indexes and a star schema for the OLAP cubes, then volume-tested it with Microsoft at their lab.

Read the case studies →

Before60+ min

After< 3 min

Processing time per client / audit engagement

What I do

From business question to working data platform.

My work sits between business strategy and technology: understanding what stakeholders need, making architecture decisions I can defend, and helping teams deliver.

Architecture

Enterprise data modeling

Conceptual, logical and physical models. OLTP in 3NF and OLAP in star and snowflake schemas, using Kimball and Inmon.

ERwin · ER/Studio · common data models

Modernization

Lakehouse and cloud platforms

Moving legacy warehouses to the cloud with Medallion architecture and modern table formats.

Databricks · Snowflake · Azure · Delta Lake · Iceberg

Integration

Pipelines and migration

Source-to-target mapping, ETL/ELT design and migrations, including two utility divestitures and a global SAP consolidation.

ADF · SSIS · Informatica

Governance

Trusted, governed data

Master and reference data, quality rules, metadata, lineage, standards and role-based security.

MDM · data quality · lineage

Analytics

BI foundations

Dimensional and semantic models, KPIs and dashboards that make self-service reporting possible.

Power BI · Tableau · SSRS · SSAS

Leadership

Evaluation and delivery

Proofs of concept, platform selection, architecture roadmaps, vendor management and globally distributed teams.

PoC / PoT · Agile · mentoring

Case studies

Selected work.

Health insuranceOngoing

An enterprise lakehouse for healthcare claims

Challenge: Move a SQL Server and Synapse warehouse to the cloud and merge claims from several processing systems.
Approach: Databricks Medallion layers; common 3NF models for medical, dental and pharmacy claims; dimensional models for eligibility and claims; a Snowflake analytics model with KPIs.
Result: One claims and coverage foundation for enterprise reporting.

Pharmacy benefitsMainframe modernization

Choosing a distributed database, with evidence

Challenge: Pick an application database for a microservices replacement of an IBM mainframe claims system.
Approach: Installed and ran a YugabyteDB proof of concept across three private-cloud data centers; built the enterprise data model; compared modeling tools and warehouse options.
Result: A platform decision grounded in tested criteria instead of vendor claims.

UtilitiesSnowflake · Azure

A cloud warehouse for a natural-gas utility

Challenge: Bring work management, customer service and financial data together, and support two divestitures.
Approach: Snowflake warehouse with facts, dimensions and roles; Azure Data Factory pipelines; inbound and outbound migrations.
Result: Power BI KPIs for customer service, safety and finance, plus real-time emergency dashboards.

PharmaField sales analytics

Replacing spreadsheets for a pharma sales team

Challenge: Field reps and managers relied on Excel reports to track performance.
Approach: A secure star-schema warehouse with role-based data restriction; Tableau Server with SAML sign-on; a re-architected prescriber call plan feeding the CRM.
Result: Performance and year-over-year views by team, product, territory and region.

Experience

Twenty-four years, ten organizations.

A path from hands-on data warehousing to enterprise architecture, cloud platforms and governance.

2024 – now

Data Architect

GEHA · health insurance

Lakehouse modernization on Databricks and Snowflake; common claims models; dimensional EDW for eligibility and claims.

2022 – 2024

Senior Data Architect

SS&C Technologies · DST Health

Mainframe modernization, YugabyteDB evaluation, enterprise data model, Power BI semantic models.

2018 – 2022

DW / BI Architect

South Jersey Industries · utilities

Snowflake warehouse, Azure Data Factory, emergency-metrics dashboards, two divestiture migrations.

2016 – 2018

Data / BI Architect

Bausch Health · pharma

Secure reporting warehouse, Tableau and Power BI for field sales, MDM and corporate DW.

2013 – 2016

Information Architect

Axalta Coating Systems · manufacturing

DW strategy for global sales and profitability, SAP consolidation, integration across SAP, Salesforce and Oracle. Projects worth over $5M.

2012 – 2013

Data Architect

KPMG · audit

eDataMining redesign; processing cut from over an hour to under three minutes.

2011 – 2012

Data Warehouse Architect

Lincoln Financial Group · retirement

Consolidated retirement and pension warehouse, Informatica ETL, BusinessObjects self-service BI.

2010 – 2011

Data Warehouse Architect

AXIS Capital · insurance

Enterprise warehouse for policy, claims and cash from ten source systems, feeding reporting and ERP.

2009 – 2010

Data Architect

EmblemHealth · health insurance

Led the Assurance of Discontinuance project, delivered on time and within budget.

2002 – 2009

Data Architect

Philadelphia Insurance Companies

Seven-plus years of data architecture for a specialty property and casualty insurer.

Industries Healthcare & health insurance Insurance & financial services Pharmacy benefits Pharma & life sciences Utilities Manufacturing

About Monish

I started in computer science and added an MBA in finance and marketing. That pairing still shapes how I work: every model I design has to answer a business question.

Over twenty years I have designed warehouses, lakehouses and analytics platforms for health insurers, a pharmacy-claims processor, a global manufacturer, a utility and an audit firm. I take a practical, hands-on approach, balancing enterprise standards with what teams can actually build and maintain.

Today I am most interested in what comes next: how well-governed enterprise data, semantic models and metadata can make AI applications and agents trustworthy.

MBA, Finance & MarketingLeBow College of Business, Drexel University

BS, Computer ScienceGujarat University, India

Insights

Building the data foundations for enterprise AI.

AI is only as trustworthy as the data beneath it. These are the questions I am writing about.

AI-ready data

Making enterprise data understandable to AI agents

Why semantic models, business definitions and metadata matter more once an agent is asking the questions.

Essay coming soon

Governance

Permissions, lineage and quality in AI workflows

Extending the governance you already have to retrieval and agentic patterns.

Essay coming soon

Modernization

What a Medallion lakehouse gets right, and where it needs help

Lessons from modeling claims across bronze, silver and gold layers.

Essay coming soon

Contact

Let's talk about your data architecture.

Whether you are modernizing a warehouse, unifying data models, strengthening governance or preparing for AI, I welcome conversations with technology leaders, hiring teams and organizations planning what comes next.

Message me on LinkedIn ↗ linkedin.com/in/monishjain