Open to Director, Head, Lead & Principal — Data Governance, Data Quality & AI-controls — Bengaluru · Remote · India & UAE / GCC · Europe (Blue Card / Critical Skills) · APAC. Executive one-pager ↓Book intro call →
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15 years · ex-FICO · ex-EY · DAMA CDMP · GDPR-aligned controls (vendor-side)

Ram Balasubrahmanian

Trusted data for regulated scale.

When regulators ask questions, boards need answers — I build the governance, controls, and audit evidence that make data defensible. 95% fewer incidents, 232M+ records protected, $10M+ ARR supported across 50+ regulated financial-services clients at FICO.

95%Incident reduction
232M+Records protectedper extraction cycle
$2M+Annual savings
50+Enterprise clients
Hiring focus

Director-level data governance & DataOps for global-bank GCC captives, DIFC/ADGM banks and UAE/KSA fintechs — and senior leadership within the function at regional banks. PDPL and NDMO build on the GDPR-aligned controls and DMBOK foundation I have delivered vendor-side. Bengaluru-based, relocating, immediate joiner.

Open toDirector / Head — Data Governance · Data Quality & DataOps · AI Controls — BFSI & other data-intensive domains
RAG & AI BuilderAnthropic · Claude · MCPNewsletter · 2,400+ subscribersex-FICO · EYDAMA CDMP PractitionerOpen to UAE · GCC · APAC · Remote

95%

Incident reduction

within 3 months

232M+

Records protected

per extraction cycle

$2M+

Annual cost saved

failure costs eliminated

50+

Enterprise clients

onboarded and governed

$10M+ ARR

Platform ARR supported

enterprise client revenue

Executive Brief

For leaders who need data they can defend in the boardroom.

I convert data risk into audited business capability — combining governance policy, engineered controls, and evidence that holds up under regulator, auditor, and CFO scrutiny.

Download executive one-pager →

Endorsement excerpt

"Metric driven and extraordinarily accountable. A rare combination of technical depth, domain knowledge, and influence."

Ken Bouley · Direct Manager, FICO · Executive Leadership
Risk95% incident reduction

Fewer production failures, faster RCA, audit-ready evidence for every escalation.

ValueOnboarding: 4 weeks → 2–3 days

Metadata-driven quality at scale — AI and analytics on trusted, governed data.

Cost$2M+ annual savings

Recurring failure costs eliminated through prevention controls, not firefighting.

FICOEYDAMA InternationalHCL Technologies

Operating Model

How production incidents become governed systems.

This is the discipline behind the 95% incident reduction — not a framework slide, but how I run data operations in production.

See proof →
01

Detect

Metadata checks, SLA signals, reconciliation, and monitoring surface anomalies before they become escalations.

02

Resolve

ServiceNow routing, RCA evidence, and clear ownership paths close incidents with audit-ready context.

03

Prevent

Shift-left gates, reusable DQ rules, and defect review boards stop recurring failures upstream.

04

Govern

Lineage, stewardship, privacy controls, and regulatory evidence attach to every operating rhythm.

05

Scale

Reusable playbooks accelerate client onboarding and quality without custom rework each time.

About

About Ram Balasubrahmanian.

I help regulated enterprises turn fragmented data operations into trusted operating systems: governed, observable, audit-ready, and built for AI adoption. Across EY and FICO, I have led where engineering reliability, governance control, regulatory evidence, and business adoption meet.

At FICO I scaled data operations for 50+ enterprise clients, reduced production incidents by 95% in three months, protected 232M+ customer records per extraction cycle, eliminated $2M+ in recurring annual failure costs, supported $10M+ in platform ARR, and compressed onboarding from 4 weeks to 2–3 days with metadata-driven quality controls.

Since April 2025 I’ve run an independent data & AI governance practice — a Data Steward engagement via Toptal, production RAG systems, and a LinkedIn newsletter to 2,400+ subscribers — after a deliberate move to support family caregiving, now well-supported. I lead in AI governance, not just advise on it. See independent-practice deliverables.

I am open to Director and Head of Data Governance leadership — data governance, data quality, DataOps, metadata, and AI controls — in BFSI & other data-intensive domains. Bengaluru-based, immediately available, across India, UAE/GCC, APAC, and remote-first global teams.

Open To

Data governance leadership across BFSI & other data-intensive domains

Core — data governance & quality

  • Director / Head — Data Governance
  • Senior Manager / Lead — Data Governance & Data Quality (banking GCC)
  • Lead / Principal / Senior Manager — Data Governance & AI Governance (Europe / EU AI Act)
  • Director / Head — DataOps, Data Quality & Metadata
  • Director — Data Quality, MDM & Metadata

Edge — AI governance & advisory

  • Director / Lead — AI & Data Governance (Responsible-AI controls)
  • Director / Head — AI Governance
  • Principal / Director — Data Governance & DataOps Advisory

Case Studies

Four proof points. One operating discipline.

95%fewer incidents
$2M+annual savings
232M+records protected
20–100 hrs→<4 hrsworst-case resolution
50+clients governed
02

Quality that scales without custom rework.

Client onboarding depended on custom validation scripts, slowing delivery and making quality controls harder to reuse.

4 wks → 2–3dclient onboarding
45%fewer escalations

AWS Athena · Python · Apache Hop · Metadata config

Executive takeawayFaster onboarding came from reusable, metadata-driven controls — not more headcount. Quality that compounds instead of resetting with every client.

03

Privacy controls at regulated scale.

As AI/ML decisioning expanded, privacy risk and audit exposure increased across ingestion, training sets, and consumption.

232M+records protected
10KTPS throughput

AWS KMS · IAM · Python · Lineage controls

Executive takeawayPrivacy became an engineered control with evidence attached — not a policy promise. Defensible the moment a regulator asks.

04

AI governance from model to evidence.

AI/ML across credit decisioning and fraud detection required stronger explainability, model-risk controls, and regulatory transparency.

Model-lifecycle governance with explainability controls, drift monitoring, challenger/champion evidence, human review gates, and regulatory documentation.

Model governance · Explainability · Python · AWS · ServiceNow

Executive takeawayAI stayed auditable from model to decision — explainability, review gates, and evidence as defaults, not afterthoughts.

50+clients governed
Fullaudit trail
RAIby default

Live Proof

Three working systems. Production AI + governed data platforms.

Most leaders talk about AI governance. These are three systems I designed and shipped — open, click, and inspect any of them right now.

New · Flagship demo

Golden Record RAG Pipeline

Entity resolution, survivorship, lineage and vector RAG for fintech compliance — live on 89,198 records. Open the live app, an animated architecture walkthrough, and a guided playbook, all in-page.

89,198source records20,502golden records35,000RAG chunks
Open demo hub →

Enterprise Data Platform

Pipeline Pulse

DMBOK-aligned platform demo — metadata-driven DQ, governance controls, lineage, and AI governance in working software.

Proves
DMBOK as working software — governance, data quality, lineage, and AI controls you can click through, not slideware.
Why it matters
It turns abstract DAMA knowledge areas into an operating picture a CDO, auditor, or steward can actually use.
Governance screens
Metadata-driven DQLineage & stewardshipAudit evidence hubRBAC / ABACAI governance
Control planeArchitecture → quality → governance → evidence → AI control

Capabilities

Four pillars. Fifteen years in production.

01

Governance & DAMA

Data governance, stewardship, DMBOK, metadata, MDM, business glossary, and audit evidence across regulated BFSI.

02

AI, RAG & Responsible ML

AI governance, RAG pipelines, model risk, explainability, Claude/Anthropic, and governed AI in production.

03

DataOps & Reliability

Detect → Resolve → Prevent → Govern → Scale, metadata-driven DQ, incident reduction, ServiceNow, and shift-left quality at scale.

04

Privacy, GDPR & AI-Act

GDPR-aligned controls delivered vendor-side for global financial-services clients — plus an EU-AI-Act-ready control plane (high-risk data governance, logging, human oversight, model controls). SOX, DPDP, ISO 27001 / SOC 2 discipline — the foundation PDPL & NDMO build on. UAE/KSA-ready · NDMO-ready via DMBOK · DORA-aligned.

Full domain breakdown in the EDP guide

Testimonials

What leaders who worked with me say.

All 11 on LinkedIn →
15SPOT Awards at FICOOutstanding performance recognition
11LinkedIn recommendationsFrom direct managers and senior peers

Experience

Fifteen years. Larger scope. The same operating discipline.

Independent Consultant — Data & AI Governance · Apr 2025 – Present

Two deliberate choices — and a year of shipped work.

In 2024, family caregiving led me to two deliberate choices: a lateral move to the senior IC track at FICO (same grade, at my request), and then — days after my FY24 increase and full bonus — a planned resignation in good standing, with the full 90-day notice served. Since April 2025 I’ve run an independent data & AI governance practice: a Data Steward engagement via Toptal, The Governed Data & AI Brief (2,400+ subscribers), production RAG systems (MediGovern, Pipeline Pulse), and the DAMA CDMP Master track (submitted May 2026). That caregiving chapter is now well-supported — and I’m deliberately returning to full-time senior leadership.

Available immediately
3live production demos
2,400+newsletter subscribers
CDMPMaster submitted 2026
6EDP learning tracks published

Family caregiving is now well-supported, and I am immediately available for Director and Head of Data Governance, Data Quality & DataOps roles in BFSI & other data-intensive domains.

Independent Consultant — Data & AI Governance

Consulting, Applied AI Governance & Thought Leadership

Apr 2025 – Present Independent practice

FICO

Senior Manager — Data Management, Enterprise Data Platform

Jun 2022 – Sep 2024 2 yrs 3 mos

  • Scaled Detect → Resolve → Prevent → Govern → Scale governance for 50+ enterprise clients, reducing production incidents 95% within three months and cutting worst-case resolution from 20–100 hours to under 4.
  • Led an 11-member governance team within a 25+ member platform organization across India, the US, and Canada — hiring, performance management, and the governance tooling roadmap.
  • Established PII safeguards and audit-trail governance protecting 232M+ regulated records per cycle; supported $10M+ ARR and delivered $2M+ annual savings.

FICO

Senior Individual Contributor (Sr. Engineer)

Oct 2024 – Mar 2025 Lateral move, at my request

  • Requested a lateral move (same grade, compensation unchanged) from people management to the senior IC track to support a family caregiving responsibility; awarded the FY24 merit increase and full bonus in Dec 2024.
  • Delivered six major DPL/ADE releases on schedule and shipped COGS-reduction capabilities; resigned Dec 2024 and served the full 90-day notice through Mar 2025 — a planned, good-standing exit.

FICO

Manager · Enterprise Data Platform, Data Operations & Governance

Dec 2018 – Jun 2022 3.5 years

  • Automated metadata-driven data quality checks using AWS Athena, Python, and Boto3 — reducing incidents by 50% in three months and onboarding clients in 2–3 days (from 4 weeks) with zero custom rework per client.
  • Governed 75GB+ batch workloads and 2.5M–3M API calls per cycle with SLA-driven processing and reconciliation controls across 50+ enterprise clients.
  • Embedded ingestion controls including control files, checksums, header/footer validation, and duplicate rejection — reducing downstream escalations by 45%.

FICO

Lead / Associate Manager · Data Management Platform

Oct 2016 – Dec 2018 2 years

  • Built enterprise ingestion, validation, transformation, and reconciliation pipelines for decisioning and analytics platforms serving global financial clients.
  • Delivered COBOL-to-JSON transformation for 3,500-column datasets, 25–35GB files, and 5M records within a 2-hour SLA.
  • Led technical reviews, RFP inputs, and client demonstrations that contributed to 6+ new enterprise clients and $5M in new ARR.

HCL Technologies

Technical Lead · Data Migration, Reconciliation & Guidewire Integration

Apr 2015 – Oct 2016 1.5 years

  • Spearheaded Guidewire Insurance Suite migrations for global teams using reusable ETL, validation, and reconciliation frameworks.
  • Built validation, cleansing, and SQL optimisation workflows for BFSI and publishing clients.

EY · Cognizant · RR Donnelley

Associate Tech Lead / Programmer Analyst / Software Engineer

Jul 2009 – Mar 2015 6 years

  • Delivered data migration, reporting, SQL automation, and enterprise application support across consulting and delivery roles.
  • Progressed from software engineering into data management, reconciliation, and platform delivery leadership — the foundation for everything that followed at FICO.

Perspectives

Perspective shaped by production work.

Case Study · DataOps

Reducing enterprise data incidents by 95% in 3 months

The answer was not more tooling. It was a disciplined operating model — Detect → Resolve → Prevent → Govern → Scale — where every failure moved from symptom to ownership, evidence, root cause, prevention, and governed scale.

Read article

Executive Perspective · AI Governance

AI governance is an operating model, not a document

Model cards matter, but they are not enough. BFSI teams need explainability, privacy checks, drift monitoring, human review, and evidence that stays current after deployment.

Read article

Regional Insight · GCC

What GCC data programs need now

Saudi Arabia's PDPL and UAE governance expectations are turning data control into an operating requirement. Policies, stewardship, lineage, and evidence need to work in production, not only on paper.

Read article

All perspectives

🏆 Official Verified Credentials

DAMA CDMP Credential Wall

DAMA International Certified Data Management Professional — three domain exams passed, Practitioner level achieved, and Master-level approval track in progress.

CDMP Practitioner Badge
🆕 JUST EARNED
DAMA International · Official Certification
Certified Data Management Professional
Practitioner Level
Credential ID20023851Date IssuedMay 22, 2026Valid UntilMay 22, 2029Signed byPeter Aiken, President · DAMA International
CDMP Certification Pathway
Associate
Foundation exam
Practitioner
Foundation + 2 Specialist
← You are here
Master
Foundation + 2 Specialist + All 3 exams >80% & Approval by DAMA
In progress
Data Management Fundamentals
Data Management Fundamentals
Foundation Exam
88%
✓ Verify Credential
Data Governance
Data Governance
Specialist Exam
83%
✓ Verify Credential
Data Quality
Data Quality
Specialist Exam
88%
✓ Verify Credential
CDMP Practitioner
CDMP Practitioner
Practitioner Level
#20023851
✓ Verify Credential
88%
Data Management Fundamentals
Mastery across all 17 DAMA-DMBoK knowledge areas. Foundation of the CDMP certification pathway.
Foundation Exam · #19686465
83%
Data Governance
Expert-level governance frameworks, stewardship, policy hierarchies, accountability and decision rights for regulated enterprises.
Specialist Exam · #19940610
88%
Data Quality
Expert proficiency in DQ frameworks, measurement methodologies, enterprise quality governance, and improvement programs.
Specialist Exam · #20023492

AI Implementation · Vibe Coding · Production RAG

Highly passionate about building governed AI in production.

I don't just advise on AI governance — I build. Completed Anthropic’s Claude & MCP certificate courses (6 Certificates of Completion), hands-on with RAG pipelines, vibe coding, and AI-assisted development. From MediGovern RAG to Pipeline Pulse, I ship working AI systems with governance built in.

Anthropic Claude CertifiedMCP · Model Context ProtocolRAG PipelinesVibe Coding / AI-Assisted DevResponsible AIProduction API Deployment

Additional certifications

Scrum Master

2025

SAFe

Agile at Scale

Guidewire

Data Hub & InfoCenter

Data-Driven Decision Making

2025

FAQ

Common questions from hiring leaders.

Who is Ram Balasubrahmanian?

Ram Balasubrahmanian is a Senior Data Governance and AI Governance leader with 15+ years across FICO, EY, and regulated BFSI platforms. He is a DAMA CDMP Practitioner who builds governed, auditable data systems for enterprise scale and AI adoption. Read full background.

Is Ram open to UAE, GCC, and APAC leadership roles?

Yes. Ram is based in Bengaluru, available immediately, and open to Director and Head-of-function mandates across data governance, AI governance, DataOps, data quality, and metadata — in BFSI & other data-intensive domains, across UAE, Dubai, Abu Dhabi, Saudi Arabia, Qatar, the broader GCC, India, APAC, and remote-first global teams. Connect here.

Can Ram lead data governance under PDPL, NDMO, and SAMA without prior Gulf tenure?

These regulations are new — UAE and Saudi PDPL and Saudi's NDMO standards are 2021–2024 in vintage — so almost no one has deep lived in-region tenure. PDPL is modelled on GDPR and NDMO maps to DAMA-DMBOK, frameworks Ram has worked with directly — GDPR-aligned controls delivered vendor-side for global financial-services clients, and DAMA-DMBOK applied across enterprise platforms (CDMP Governance 83%, Data Quality 88%). He brings the proven parent control plane — 232M+ records protected with audit-ready evidence — and can stand up a PDPL- and NDMO-aligned operating model fast. Strongest fit: global-bank GCC captives, DIFC/ADGM banks, and UAE/KSA fintechs. Read the GCC & PDPL crosswalk.

Can Ram lead EU data governance under GDPR, the EU AI Act, and DORA without prior European tenure?

Unlike most relocating candidates, GDPR is not a framework Ram learned for an exam — he has delivered GDPR-aligned controls from the vendor side for global financial-services clients (classification, masking, lineage, audit evidence), plus published GDPR/EU-AI-Act advisory analysis and working demos. He has also built the kind of AI controls the EU AI Act now mandates — data governance, logging, human-oversight gates and model controls — which you can open as three live demos. The gap is European residence, not European regulation: he is relocating, visa-ready (EU Blue Card / NL Highly Skilled Migrant / Ireland Critical Skills / Germany Opportunity Card), and targets English-first employers — global-bank EU hubs, scaled fintechs and consultancies. Read the EU GDPR & AI-Act crosswalk.

What has Ram been doing since leaving FICO?

In 2024, family caregiving led Ram to request a lateral move at FICO (same grade, senior IC track); days after his FY24 merit increase and full bonus, he resigned in good standing and served the full 90-day notice through Mar 2025. Since Apr 2025 he has run an independent data & AI governance practice — a Data Steward engagement via Toptal, and he shipped MediGovern RAG and Pipeline Pulse, grew The Governed Data & AI Brief to 2,400+ subscribers, published the EDP knowledge hub, and submitted the DAMA CDMP Master track (2026). See independent-practice deliverables.

What measurable outcomes has Ram delivered?

At FICO: 95% incident reduction in 3 months, 232M+ records protected per extraction cycle, $2M+ annual failure costs eliminated, and onboarding from 4 weeks to 2–3 days through metadata-driven quality controls across 50+ enterprise clients. Driven by the Detect → Resolve → Prevent → Govern → Scale operating model. Read the case study.

What is Ram's approach to AI governance?

AI governance as an operating model — not a document. Model lifecycle controls, explainability evidence, privacy checks, drift monitoring, human review gates, and audit trails embedded in production rhythm. Read the AI governance perspective.

Does Ram build RAG and production AI systems?

Yes. Ram built MediGovern RAG — a full retrieval-augmented generation pipeline with production API and open-source code. He holds 6 Anthropic Claude & MCP Certificates of Completion and is passionate about governed AI in production. See demos.

Where can I see working proof beyond the resume?

Ram built MediGovern RAG, Pipeline Pulse, and publishes The Governed Data & AI Brief(2,400+). Explore full guides · Live demos.

Contact

Let’s talk about the data outcomes you need next.

In 30 minutes, we can map your governance, AI, or DataOps challenge to the operating models I have built across FICO, EY, and regulated BFSI platforms.

What happens in 30 minutes

  • You outline the governance, AI, or platform outcome you need
  • I map it to directly relevant operating experience
  • We assess fit against your team structure and seniority level
  • You leave with a clear view of the value I can bring
Availability Available immediately · Relocating to the Gulf and to Europe — available to interview in-region or on EU hours, immediate joiner · GCC: open to work-permit / iqama sponsorship (UAE · Dubai · Abu Dhabi · KSA · Qatar) · Europe: EU Blue Card / Netherlands Highly Skilled Migrant / Ireland Critical Skills / Germany Opportunity Card · also India · APAC · Global remote · Director & Head (India, GCC, APAC) or Lead / Principal / Senior Manager (Europe) — Data Governance, Data Quality, DataOps, and AI-governance roles in BFSI & other data-intensive domains.

Book a 30-min intro call

Pick a time below — or email ram@ram-bala.com

Or send a brief note