Kumar Komal Kant

• Data & AI Strategy: Define enterprise Data & AI vision, operating model, roadmap, platform strategy, data product priorities, operating model, investment priorities, value scorecards, architecture standards, and quarterly executive portfolio reviews and AI adoption governance aligned with business value.
• Commercial & Budget Leadership: Build TCO/ROI cases, multi-year platform investment roadmaps, cloud spend controls, vendor/license rationalization plans, RFP/RFI, TCO/ROI, budget scenarios, cost optimization, contract utilization, investment prioritization and executive value scorecards.
• AI Transformation: Lead GenAI, RAG, agentic analytics, enterprise search, document intelligence, semantic search, LLM evaluation, forecasting, analytics automation, decision-support use cases, and AI governance from ideation to controlled adoption.
• Enterprise Data Platforms: Modernize legacy data warehouses and Hadoop platforms into AWS/Azure/GCP, Snowflake, Databricks, Microsoft Fabric, Redshift, Delta Lake, Iceberg, medallion Lakehouse patterns, reusable patterns, data contracts, security guardrails, privacy controls, AI risk reviews, and production readiness checklists.
• Governance, Risk & Compliance: Establish data governance, AI governance, glossary, metadata, lineage, quality, MDM, RBAC, privacy, auditability, GDPR, HIPAA, UAE PDPL, NDMO, and PDP-aligned controls.
• Leadership & Delivery: Lead cross-functional matrix teams across data engineering, AI/ML, BI, cloud, security, DevOps, PMO, vendors through structured roadmaps, agile delivery, quality gates and executive stakeholders.

• Spearheaded the development of scalable distributed data solutions leveraging Snowflake and Hadoop, focusing on architecture design and capacity planning.
• Led the assessment of technical vendors and managed the RFP process, ensuring alignment with project goals.
• Engineered complex data flows within Banking and Finance systems, implementing innovative strategies for optimized, future-proof solutions.
• Collaborated effectively with stakeholders, business analysts, development teams, and external vendors to gather business requirements and translate them into actionable technical specifications.
• Fostered strong relationships across teams to ensure seamless communication and project success.

• Led the implementation of data retention procedures and business disaster recovery (BDR) strategies, ensuring optimal data availability and secure user access to Hadoop clusters.
• Collaborated effectively on performance testing plans, providing strategic recommendations for infrastructure setups aligned with data solution architecture.
• Showcased advanced skills in installing, configuring, and managing Hadoop clusters using Apache, including the establishment of local CDH repositories (CDH5, CDH6, CDP) and Yarn distributions.
• Transitioned from a Senior Technical Lead to a Solutions Architect role, leveraging deep technical expertise to design scalable, efficient data solutions.
• Engaged cross-functional teams to drive innovative solutions, enhancing overall system performance and user experience.

• Designed and implemented scalable distributed data solutions leveraging Hadoop, enhancing data processing efficiency.
• Led architecture design and capacity planning, ensuring robust and scalable solutions aligned with business needs.
• Successfully spun up production environments using CDH 5.12.x in AWS via Cloudera Director, optimizing service configurations.
• Installed and configured Cloudera Director in AWS, streamlining environment creation through template development.
• Established and configured databases to RDS instances, improving data accessibility and performance.
• Deployed and configured Cloudera Data Science Workbench, facilitating advanced analytics capabilities.
• Collaborated with data science teams to drive data-driven decision-making and innovative solutions.

• Designed and implemented robust database solutions for multiple RDBMS and NoSQL platforms, enhancing data accessibility and performance.
• Developed and optimized complex PL/SQL queries, stored procedures, and functions, significantly automating critical business processes.
• Collaborated with cross-functional teams to understand requirements and translate them into scalable database architectures.
• Leveraged best practices in database design and management to ensure data integrity and security.
• Contributed to the overall efficiency of systems, resulting in improved response times and reduced operational costs.
• Continuously evaluated emerging technologies to recommend innovative solutions for database challenges.