Sreekanth Kumar V L N

Enterprise Data, AI & Data Governance Architect with 14+ years of experience delivering enterprise-scale digital transformation, Data Governance, AI/ML, GenAI, and cloud modernization initiatives across BFSI, Telecom, Energy, CPG, Insurance, Manufacturing, and Retail domains. Proven expertise across the full project lifecycle including requirement gathering, business analysis, solution architecture, development, CI/CD deployment, UAT, business handover, and post-go-live support, ensuring seamless execution in regulated enterprise environments. Specialized in architecting AI-driven governance solutions leveraging Multi-Agentic AI systems, Retrieval-Augmented Generation (RAG), Generative AI, Agentic AI, and AI/ML, enabling intelligent automation of data classification, policy validation, remediation workflows, metadata management, and compliance operations.

Extensive experience designing enterprise Data Governance frameworks covering metadata management, business glossary, data lineage, data quality, stewardship, MDM, data privacy, risk management, regulatory compliance, and Responsible AI, establishing trusted and business-ready data ecosystems. Strong capability in translating complex business and regulatory requirements into scalable, secure, and automated governance solutions, delivering measurable customer value through reusable accelerators, prompt libraries, templates, and AI-enabled automation frameworks. Experienced in building and modernizing cloud-native data platforms using Azure Databricks, Snowflake, Azure Synapse Analytics, Azure Data Factory, Microsoft Purview, AWS, and hybrid cloud environments, ensuring high availability, performance optimization, security, and operational excellence.

Trusted advisor to CXOs and executive stakeholders, with a proven track record of aligning Data, AI, and Governance roadmaps with digital transformation goals, driving operational efficiency, cost optimization, regulatory readiness, and data-driven decision-making. Accomplished leader of large cross-functional and globally distributed teams, providing strategic, technical, and functional leadership across architecture governance, stakeholder management, innovation, delivery excellence, mentoring, and customer success.

Solution Architect - DXC Technology

(2025-12)

• Lead enterprise Data, AI, and Data Governance transformation initiatives by defining target-state architecture, Data Strategy, AI Strategy, and governance operating models aligned with business objectives.
• Architect and deliver cloud-native Data, AI/ML, and GenAI solutions using Azure Databricks, Snowflake, Azure Synapse Analytics, Azure Data Factory, Microsoft Purview, and Azure AI Services.
• Design enterprise Data Governance frameworks covering metadata management, business glossary, data lineage, data quality, stewardship, MDM, data privacy, risk management, and regulatory compliance.
• Develop Multi-Agentic AI and RAG-based solutions for automated data classification, policy validation, compliance monitoring, remediation workflows, and intelligent knowledge retrieval.
• Oversee CI/CD deployment, release management, Dev-to-Production migrations, performance optimization, RCA, and production stabilization to ensure high availability and business continuity.

Data Governance Architect / GenAI Lead - Tiger Analytics

(2024-10 - 2025-11)

• Spearheaded enterprise Data Governance and AI transformation programs across BFSI, Telecom, Energy, and CPG sectors, translating regulatory and business requirements into scalable governance solutions.
• Architected and deployed Generative AI, Agentic AI, and RAG-based solutions using Azure Databricks, Snowflake, Azure Synapse Analytics, Azure Data Factory, Azure AI Services, and Vector Databases.
• Implemented AI-augmented governance capabilities including automated PII detection, metadata tagging, data quality scoring, compliance monitoring, and reusable accelerators.
• Established CI/CD pipelines, managed release cycles, cloud deployments, production stabilization, and performance engineering to ensure seamless delivery.
• Defined ROI metrics, conducted UAT, training, knowledge transfer, and business handover activities for successful production rollout.

Principal Consultant - Birlasoft

(2023-11 - 2024-10)

• Advised enterprise clients on Data Strategy, Data Governance, AI adoption, Cloud Modernization, and Digital Transformation initiatives.
• Designed enterprise Data Governance frameworks and scalable cloud data platforms using Azure Databricks, Snowflake, Azure Synapse Analytics, Azure Data Factory, Microsoft Purview, and Power BI.
• Architected RAG-based AI governance solutions for intelligent search, compliance Q&A, policy assistance, and audit support.
• Led architecture workshops, technology roadmaps, cloud deployments, Dev-to-Production migrations, release governance, and operational optimization.

Software Manager II - Quest Software

(2015-07 - 2023-09)

• Directed enterprise Data Governance, Data Architecture, Data Modernization, and Cloud Transformation programs for global BFSI, Insurance, Telecom, Manufacturing, and Retail clients.
• Designed governance frameworks covering metadata management, data lineage, data quality, stewardship, MDM, data privacy, risk management, and regulatory compliance.
• Architected enterprise Data Lake, Lakehouse, AI/ML, and Cloud Analytics platforms using Azure Databricks, Snowflake, Azure Synapse Analytics, Azure Data Factory, Microsoft Purview, Hadoop, Hive, and SQL.
• Led Multi-Agentic AI and RAG-based governance solutions, CI/CD implementation, cloud migrations, DevOps, release management, production support, and performance optimization.
• Managed globally distributed teams and partnered with executive leadership on enterprise architecture, cloud adoption, and modernization roadmaps.

ETL Developer - Diyotta

(2013-07 - 2015-07)

• Designed and developed ETL and Data Warehouse solutions using Informatica, Oracle, DB2, SQL Server, Netezza, and Hadoop.
• Built scalable data integration pipelines, optimized ETL workflows, and improved data quality and processing efficiency.
• Supported requirement analysis, development, testing, deployment, Dev-to-Production migrations, production support, and performance tuning.

Advanced AI, Machine Learning & Deep Learning - IIT Delhi

Bachelor of Technology (B.Tech.) - Electronics & Telecommunication Engineering - JNTU College of Engineering, Hyderabad (2007 - 2011)