Headline

Senior Data Engineering Leader | Data Platform Architect | Enterprise Lakehouse & AI-Ready Platforms | Ex-HSBC, Maybank

About

Strategic, business-focused Senior Data Engineering Leader and Platform Architect with 15+ years of success designing petabyte-scale Data Lakehouse environments and steering high-performing global engineering teams across tier-1 financial institutions. Recognized expert in Google Cloud Platform (GCP) data design, FinOps cloud cost governance, and building enterprise-grade, AI-ready feature platforms to accelerate GenAI and Machine Learning frameworks. Trusted advisory partner to global C-suite, Risk, and Finance executives, translating complex cross-functional business needs into secure, scalable, cost-efficient data architectures that align directly with stringent international regulatory frameworks (BCBS 239, IFRS, IRB) and corporate revenue milestones

Location

Bengaluru

AI stack

claude code

claude

gemini

openai

Work experience

Senior Data Engineering Manager at NAM Info Inc, May 2026 - Present · 6 mos, Bengaluru, Karnataka, India, 🚀 Project: Enterprise AI & ML Feature Pod Platform Problem: Disconnected feature engineering steps across teams were delaying Machine Learning (ML) and Generative AI time-to-market and blowing out GCP compute limits. Impact: Architected a modular Feature Pod ecosystem on Google Cloud. This enabled rapid pipeline reuse across teams, cutting model deployment timelines by 40% and ensuring complete governance for LLM applications. 🏗️ Project: Petabyte-Scale Medallion Lakehouse Transformation Problem: Fragmented data sources caused complex pipelines, high query latencies, and unreliable downstream analytics data. Impact: Led the end-to-end design and deployment of a secure GCP Medallion Data Architecture. Unified batch and real-time processing streams, which slashed overall processing latency by 30% and reduced query costs through automated warehouse partitions. 👥 Initiative: Global Engineering Delivery & Stakeholder Alignment Problem: Lack of centralized engineering standards across cross-functional domains caused delayed compliance reporting and unpredictable software release cycles. Impact: Provided cross-functional technical management to global agile engineering squads. Unified delivery roadmaps across Risk, Analytics, and Finance teams, accelerating pipeline delivery velocity by 25% while mentoring junior managers

Assistant Vice President – Data Engineering Architect at HSBC, Sep 2021 - Apr 2026 · 4 yrs 8 mos, Bengaluru, Karnataka, India, 🏛️ Project: Cross-Region GCP Data Lakehouse Modernization Problem: Fragmented on-premises infrastructure delayed critical IFRS and regulatory reporting timelines across UK, MENA, and ASP banking sectors. Impact: Architected and scaled a centralized enterprise GCP Data Lakehouse platform. Re-engineered batch and near-real-time streaming infrastructure using BigQuery, Dataflow, and Dataproc, which boosted reporting processing speeds by 35% and ensured strict compliance with global data standards. 🛡️ Project: Decentralized Data Mesh Quality & Lineage Automation Problem: Lack of unified data lineage and automated controls across global regions exposed the bank to high operational and regulatory data risks. Impact: Engineered and automated a centralized Data Mesh governance framework. Built proactive data quality monitoring, automated lineage tracking, and metadata cataloguing across 3 global regions, eliminating manual business-as-usual (BAU) checks by 80% and mitigating data compliance risks. 🛡️ Project: Enterprise Global Data Quality Automation & Governance Framework Problem: Fragmented data ownership and manual quality checks across multiple global banking regions created operational friction and heightened compliance risks under strict financial regulations. Impact: Led the strategic design and automation of an enterprise-grade Data Mesh governance framework on GCP. Established clear data ownership, unified metadata catalogs, and automated data lineage tracking across UK, MENA, and ASP regions. Results: Migrated legacy on-premises data quality platforms to a proactive cloud-native model, eliminating manual business-as-usual (BAU) data quality checks by 80%, mitigating regulatory compliance risks, and giving C-suite stakeholders complete confidence in reporting data.

Senior Manager – Data Engineering Lead at Maybank, Sep 2018 - Aug 2021 · 3 yrs, Bengaluru, Karnataka, India, 🏗️ Project: Regional Credit Risk Data Lake Consolidation Problem: Siloed cross-border data systems delayed critical computing timelines for complex regulatory calculations (such as Expected Credit Loss [ECL], PD, and LGD parameters) across APAC markets. Impact: Led the product engineering and architecture of a centralized Enterprise Credit Risk Data Lake. Unified batch ingestion framework lifecycles across diverse legacy source systems, creating a single source of truth for IFRS 9, IRB, and Stress Testing data streams. Results: Streamlined month-end financial reporting cycles across multiple countries while providing full lifecycle visibility from ingestion to governance. ⚙️ Project: Automated Reconciliation & Back-Testing Engine Problem: Missing real-time validation checks within risk reporting streams caused data mismatches between risk and finance analytics. Impact: Developed and deployed automated pipeline verification and back-testing analytics engines using high-performance Python and SQL scripts. Results: Eradicated downstream data mismatches, accelerated stress-testing audit trails, and achieved 100% adherence to financial compliance standards during external audit sweeps. 👥 Initiative: Cross-Functional Risk-Finance Data Architecture Strategy Problem: Misaligned tech roadmaps between distributed data teams and chief risk officers frequently delayed product updates and regulatory submissions. Impact: Supervised the complete agile delivery lifecycle by partnering directly with Risk, Finance, and Analytics business leaders to define strict data definitions and capabilities. Results: Spearheaded technical mentoring programs across the broader engineering team, helping scale up overall data warehouse standards and data product quality.

Lead – Data Engineering & Analytics Platform Engineer at Satwic Inc, Aug 2010 - Aug 2018 · 8 yrs 1 mo, Bengaluru Area, India, 🎬 Project: High-Volume Media Analytics & ETL Pipeline Transformation Problem: Massive daily spikes in transactional media data from global business lines caused data delivery delays, stalling critical financial dashboards and daily executive reports. Impact: Architected, designed, and optimized high-performance, end-to-end ETL/ELT data pipelines using Informatica, DataStage, and SQL Server for large-scale data ingestion and aggregation. Results: Eliminated downstream data latency, ensured consistent data availability for corporate financial reporting, and enabled executive teams to make fast, data-driven decisions. ⚙️ Project: Data Quality Control Automation & Query Optimization Problem: Unpredictable source data formats and unoptimized SQL queries led to pipeline pipeline instability, processing bottlenecks, and frequent reporting SLA failures. Impact: Designed and deployed robust automated data validation and control frameworks to check data accuracy, completeness, and consistency before loading. Led global query optimization initiatives across the core database systems. Results: Dramatically enhanced overall data warehouse reliability, slashed pipeline compute resources, and achieved a 99.9% SLA adherence rate for all corporate reporting data. 👥 Initiative: High-Availability Platform Support & Engineering Mentorship Problem: Inefficient incident tracking and lack of clear documentation on legacy codebases slowed down data platform support, threatening global business operations. Impact: Led the production support engineering team, establishing agile tracking standards, runbooks, and proactive alerting mechanisms. Personally mentored junior engineers on database tuning, SQL optimizations, and delivery best practices. Results: Significantly reduced mean-time-to-resolution (MTTR) for critical incidents, improved pipeline stability, and successfully leveled up the delivery output of the engineering squad.

Education

M.C.A, Computer Science, New Horizon College of Engineering

BCA, Computer Science, Sri Dharmasthala Manjunatheshwara College, Ujire-574240, Belthangady