Fluent in both the boardroom
and the semantic model.
I'm an enterprise technology and AI consultant with 22+ years turning complex data programs into governed platforms and executive clarity. I've led a $250M transformation across 50+ brands in 20+ countries, and today I architect and deliver healthcare payer and RWE analytics on Snowflake and Power BI — owning everything from the data model to the CEO sign-off.
Sriram Anantha Padmanaban is an enterprise technology and AI consultant with 22+ years delivering data, analytics, and platform programs for global retail, financial services, and — most recently — healthcare payer and evidence-generation organizations.
He operates at the intersection where most transformations fail: between C-suite intent and engineering reality. He is equally credible chairing a steering committee and architecting a Power BI semantic model or a Snowflake cohort pipeline — which is precisely why he is trusted to own delivery risk end to end.
His current focus is healthcare RWE / HEOR and payer analytics, where he leads concurrent engagements on Snowflake, Power BI, and Azure while running disciplined program governance — JIRA hierarchies, WBS-driven planning, RACI, and Center-of-Excellence frameworks.
Technology Philosophy
Architecture is a business decision wearing an engineering costume.
The best technical choice is the one that survives contact with governance, cost, and the people who have to run it on a Monday morning. I optimize for a single source of truth, security that is designed in rather than bolted on, and semantic models a CEO can trust without a translator.
I distrust complexity for its own sake. An 80-measure model that replaces a 380-measure one is not a smaller deliverable — it is a clearer decision-making instrument. I bring the same discipline to AI: adoption succeeds when it augments human judgment, not when it replaces the accountability behind it.
Leadership Philosophy
De-risking delivery is the most valuable thing a leader can do.
Programs rarely fail for lack of talent; they fail at the seams — between workstreams, vendors, and the C-suite's understanding of where the money actually is. My job is to make those seams visible early: a five-level WBS, a RACI everyone signs, and executive reporting that tells the truth in one page.
I lead small, fast-moving teams the way I lead enterprise programs — with clarity about scope, honesty about risk, and a bias toward shipping. Trust is earned by predictability, and predictability is engineered.
What I bring to an engagement
Healthcare Data & Payer Analytics
- • HEOR / RWE program management for biopharma evidence generation
- • Medicare/Medicaid cohort & member-month analytics (PMPM, MM)
- • HEDIS-adjacent quality measures — PPC, Well-Child, Immunizations
- • IP/ED utilization methodology & denominator governance
- • HITRUST-context delivery through compliance-first partners
Enterprise Analytics Architecture
- • Power BI semantic modeling (PBIP, DAX) at enterprise scale
- • Snowflake, Azure Synapse, Databricks, Data Factory, Oracle ADW
- • Row-Level & Object-Level Security (RLS / OLS) governance
- • Legacy federation & platform rationalization
- • Executive reporting layers CIOs and CEOs trust
Technical Program Leadership
- • JIRA hierarchies — EPIC / Story / Task / Sub-Task
- • Five-level WBS as a single source of truth for scope & effort
- • Agile / Scrum / Kanban, release & change management
- • RACI, risk governance, and critical-path management
- • Center-of-Excellence design and delivery standards
AI Transformation & Product
- • AI patient identification & care-gap closure workflows
- • Clinical screening and automated scheduling capabilities
- • AI readiness strategy for human-centered adoption
- • Product architecture on Next.js, Laravel, MongoDB, Cloudflare R2
- • Founder of an AI product studio and a wellbeing movement
C-Suite Advisory & Governance
- • C-suite executive reporting (RAG, milestones, risks, decisions)
- • Steering committee facilitation & board-ready narratives
- • Vendor management — Microsoft, Oracle, Algonomy, BlueYonder
- • Budget governance across $30M+ cumulative portfolios
- • Cross-functional coordination in small, fast-moving teams
Cloud Data & Modernization
- • Azure Data Lake consolidation of 50+ sources
- • Modern data stack: dbt, DuckDB, TUVA health-data model
- • Legacy decommissioning with hard-dollar savings
- • Batch-to-near-real-time reporting modernization
- • License and data-footprint optimization
MBA, Finance
Symbiosis Institute of Management Studies, Pune
B.Sc., Applied Sciences (Computer Technology)
Coimbatore Institute of Technology