AI-Powered Data Governance Leader

Bringing AI into the heart of data governance.

CURRENT — Executive Director / Senior Data Architect, Data Quality & Governance · Wells Fargo

15+ years modernizing regulated data ecosystems — now applying machine learning and generative AI to anomaly detection, exception management, governance documentation, impact analysis, and self-service decision support across banking, commercial lending, regulatory reporting, and post-M&A integration.

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01

AI-Driven Governance Framework

Four stages where machine learning and generative AI are embedded directly into governance operations — replacing manual review cycles with AI-assisted, audit-ready workflows.

STAGE 01

Detect

ML-enabled monitoring and anomaly-detection frameworks in Python and Azure Data Factory surface pipeline failures and reporting variances before they reach downstream systems.

Python · Azure ML · Azure Data Factory
STAGE 02

Document & Map

Microsoft Copilot and generative AI draft and standardize governance artifacts, accelerating lineage mapping and impact analysis — while SME review and control ownership stay firmly in place.

Microsoft Copilot · wGenerative AI
STAGE 03

Triage Exceptions

AI-assisted exception-management patterns help business users identify anomalies, prioritize remediation, and anticipate emerging data quality risks through self-service analytics.

Power BI · Power Apps · Alteryx
STAGE 04

Govern & Report

Automated controls and AI-drafted documentation feed regulatory-reporting workflows across BCBS 239, FR Y-14, 2052a, SR 14, and AUC/A — cutting manual effort and cycle time by ~50%.

Collibra · SAS · Regulatory Controls
02

Core Expertise

AI/ML-Enabled Data Quality Generative AI & Microsoft Copilot Enterprise Data Architecture Cloud Modernization Data Governance, Metadata & Lineage Canonical & Semantic Modeling Regulatory Data Controls Analytics & Executive Reporting Data Engineering & Integration M&A Data Consolidation Automation & Orchestration Agile, DevOps & Stakeholder Leadership
03

Leadership Impact

GenAI Acceleration

Used Microsoft Copilot and generative AI to accelerate governance documentation, lineage mapping, impact analysis, and regulatory reporting — cutting manual effort and cycle time by ~50%.

ML Monitoring

Designed ML-enabled monitoring and anomaly-detection frameworks in Python and Azure Data Factory to catch pipeline failures and regulatory-reporting variances before downstream impact.

Self-Service Analytics

Built AI-assisted exception-management and self-service analytics capabilities that helped business users identify anomalies and prioritize remediation.

Regulatory Scope

Led enterprise data-quality and governance transformations across regulated banking environments, including BCBS 239, FR Y-14, 2052a, SR 14, and AUC/A.

04

Professional Experience

Executive Director / Senior Data Architect — Data Quality & GovernanceACTIVE Jan 2021 — Present
Wells Fargo
  • Lead enterprise data-quality transformation and governance initiatives spanning cloud data platforms, regulatory reporting, metadata, lineage, ontology/taxonomy, and audit remediation.
  • Automated monitoring, control workflows, and remediation processes — reducing manual staffing needs by ~50% and improving program ROI by 70%.
  • Applied Microsoft Copilot and generative AI to draft and standardize governance artifacts, accelerate lineage and impact analysis, and support regulatory-reporting documentation while retaining SME review and control ownership.
  • Developed Python- and ML-based monitoring patterns with Azure Data Factory to detect pipeline anomalies, data-quality discrepancies, and reporting variances earlier in the data lifecycle.
  • Created executive and self-service analytics solutions using Power BI, Power Apps, Tableau, SAS, and Alteryx, improving transparency and access to trusted decision-ready insights.
  • Delivered reusable canonical and semantic models supporting scalable integration, consistent business definitions, and governed analytics across data domains.
TECHNOLOGY — Azure Data Factory, Azure ML, Python, SQL, Power BI, Power Apps, Microsoft Copilot, SAS, Alteryx, Tableau, Salesforce, Collibra, Claude Cowork, N8N
Vice President / Analytics Manager / Senior Data Architect Oct 2017 — Dec 2020
Wells Fargo
  • Led enterprise-scale migration and integration programs for Commercial and Wholesale Lending platforms, improving scalability, cross-system consistency, and business continuity during post-M&A harmonization.
  • Implemented automated data-quality controls and AI-assisted exception handling, reducing manual monitoring and validation effort by ~30%.
  • Partnered with data owners and stewards to define business and technical metadata, taxonomy, conformed datasets, and risk-analysis requirements across the commercial banking domain.
  • Directed proof-of-concept evaluations for AtScale and Splice Machine and advised on fit with enterprise data and analytics architecture standards.
TECHNOLOGY — Salesforce, Alteryx, SAS, Spark, Talend, Azure, AtScale, Erwin, Oracle, Teradata, SQL Server, Collibra, MapR
Vice President / Senior Data Architect — Data Governance Leader Aug 2013 — Sep 2017
BNY Mellon
  • Modernized regulatory data-governance operations through workflow automation, standardized controls, and continuous improvement, reducing manual monitoring requirements by ~45%.
  • Strengthened metadata, data quality, and audit-readiness practices aligned with BCBS 239, SR 14, internal standards, and DAMA principles; connected business glossary terms and taxonomy to technical metadata.
  • Led client-reporting initiatives across hybrid platforms and resolved critical data-pipeline, performance, and coding issues while maintaining delivery commitments and stakeholder alignment.
TECHNOLOGY — Python, Erwin, Oracle, Teradata, SQL Server, Informatica, Collibra, Vertica, Cassandra, GitHub, Jenkins, Private Cloud
Vice President / Business Intelligence Specialist / Data Architect Jun 2012 — Jul 2013
JPMorgan Chase
  • Led CAAR analytics work within the SPG Analytics group, designing and executing controls that maintained accurate, current RMBS market data.
  • Automated RMBS workflows and validation checks, reducing manual effort by ~35% while improving reliability and operational efficiency.
  • Built resilient data pipelines and partnered with business, risk, and compliance stakeholders to define KPIs, performance measures, and acceptance criteria.
TECHNOLOGY — Data Governance practices, Python, Erwin, Oracle 11g, Teradata, SQL Server, Informatica, Vertica
05

AI, Data & Technology Skills

AI/ML & Generative AI

Copilot ML models, anomaly detection, AI-assisted data-quality and exception-management patterns, Microsoft Copilot, generative-AI-enabled documentation, lineage, impact analysis and reporting, Azure ML, Claude Cowork, N8N.

Data Architecture & Governance

Conceptual, logical, and physical modeling, canonical and semantic models, ontology/taxonomy, metadata, lineage, business glossary, data quality, MDM, DAMA, Collibra, Informatica DQ/MDM, Erwin.

Cloud & Data Engineering

Azure, AWS, Databricks, Azure Data Factory, Spark, Hadoop, Talend, Informatica, Alteryx, orchestration, batch and real-time integration.

Databases & Analytics

SQL Server, Oracle, Teradata, PostgreSQL, MySQL, MongoDB, Snowflake, Cassandra, Power BI, Tableau, SAS, MicroStrategy, Business Objects.

Programming & DevOps

Python, SQL, T-SQL, PL/SQL, JavaScript, Java, shell scripting, GitHub, Jenkins, JIRA, CI/CD.

Enterprise Applications

Salesforce Sales Cloud and Service Cloud, Siebel, InfoLease, SAP.

06

Education & Credentials

Master of Technology (M.Tech), Computer Science & Technology
Osmania University, India
M.TECH
Bachelor of Technology (B.Tech), Mechanical Engineering
NIT Warangal (formerly RECW), India
B.TECH
Certifications & Training
Oracle Certified Professional · Salesforce · MicroStrategy · SAP Basis · Talend
CERTS

Let's talk data.

Open to conversations on data governance, AI-enabled data quality, and enterprise platform modernization.

jagadeeswar.bomma@gmail.com
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