Srihari Natva

CTO

Bengaluru, Karnataka, India19 yrs 7 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

18+ years of experience in data engineering and AI.
Expert in building scalable, AI-ready data ecosystems.
Proven track record in leading global engineering teams.

Stackforce AI infers this person is a Fintech Data Engineering Leader with a strong focus on AI and cloud-native solutions.

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Skills

Core Skills

Data EngineeringAi EnablementData IntegrationEtl DevelopmentData ManagementData Governance

Other Skills

Leadership & Team BuildingTechnical ExpertiseApache SparkApache AirflowCloud ComputingData-as-a-ServiceAPI DevelopmentOracle DatabasePython (Programming Language)InformaticaPL/SQLInformatica CloudOracle ExadataOracleData Transformation

About

Senior Technology Lead and Data Executive with 18+ years of global experience leading enterprise data platform engineering, AI enablement, and large-scale transformation across banking and financial services in the United States and India. My focus is building scalable, resilient, and AI-ready ecosystems that power analytics, regulatory reporting, intelligent automation, and GenAI use cases across the enterprise. My expertise spans enterprise data architecture, modern data engineering, distributed processing (Spark), real-time streaming (Kafka), workflow orchestration (Airflow), Data-as-a-Service (DaaS) APIs, and metadata-driven governance. I specialize in modernizing legacy platforms into cloud-enabled, API-first, event-driven architectures that support secure, governed, and standardized data access for large-scale downstream consumption. A key area of impact has been enabling AI and GenAI adoption by building trusted, high-quality datasets and LLM-ready pipelines to support Retrieval-Augmented Generation (RAG), intelligent insights, and automated reporting. I work closely with data science and AI teams to embed lineage, metadata, and governance into core platform design—ensuring responsible, scalable AI implementation. Beyond architecture, I build and scale high-performing global engineering teams. I lead multi-region delivery models, mentor senior engineers and architects, and align technology strategy with business, risk, and regulatory priorities. My leadership philosophy is simple: own outcomes end-to-end, drive measurable value, and build platforms that are scalable, secure, and future-ready.

Experience

Bank of america

2 roles

VP, Senior Engineer Technology

Oct 2024 – Present · 1 yr 5 mos

Designed and delivered scalable, cloud-native data engineering architectures integrating SQL and NoSQL databases, big data platforms, and distributed processing frameworks such as Apache Spark.
Built end-to-end data pipelines for ingestion, transformation, and storage of structured and semi-structured data from databases, APIs, files, and streaming sources using Apache Airflow, Spark jobs, and custom orchestration frameworks on cloud platforms.
Defined and optimized data models and schema designs to support OLTP, OLAP, reporting, and near real-time analytics with high performance and scalability.
Optimized cloud storage and compute resources using partitioning, indexing, compression, caching, and data lifecycle management to improve performance, reliability, and cost efficiency.
Implemented data quality, validation, profiling, anomaly detection, and reconciliation frameworks to ensure data accuracy, consistency, and completeness across enterprise systems.
Designed and developed Data-as-a-Service (DaaS) APIs providing governed, standardized, and secure data access for downstream applications, analytics platforms, and business users.
Enabled AI and GenAI use cases by curating high-quality, trusted datasets for machine learning models and building LLM-ready data pipelines to support retrieval-augmented generation (RAG), intelligent insights, and automated reporting.
Collaborated with data science and AI teams on metadata-driven logic generation, data lineage analysis, and embedding structured enterprise data for GenAI applications.
Monitored and optimized data pipeline performance using cloud-native monitoring and logging tools, proactively identifying bottlenecks and improving fault tolerance and reliability.
Partnered with business stakeholders, data engineers, and analysts to translate business requirements into scalable, data-driven, and AI-ready architecture solutions.

Leadership & Team BuildingTechnical ExpertiseData EngineeringAI Enablement

VP, Feature Lead Technology

Aug 2016 – Oct 2024 · 8 yrs 2 mos

Designed and delivered scalable, cloud-native data engineering solutions integrating SQL and NoSQL databases, big data platforms, and distributed processing frameworks such as Apache Spark.
Built end-to-end data pipelines for ingestion, transformation, and storage of structured and semi-structured data from databases, APIs, files, and streaming sources using Apache Airflow, Spark jobs, and custom orchestration frameworks deployed on cloud infrastructure.
Optimized cloud storage and compute using partitioning, indexing, compression, caching, and lifecycle management to balance performance, reliability, and cost efficiency.
Implemented robust data quality, validation, profiling, anomaly detection, and reconciliation frameworks to ensure data accuracy, consistency, and completeness across enterprise systems.
Designed and implemented Data-as-a-Service (DaaS) APIs enabling governed, standardized, and secure data access for downstream applications, analytics platforms, and business users.
Enabled AI and GenAI use cases by curating high-quality, trusted datasets for machine learning models and building LLM-ready data pipelines to support retrieval-augmented generation, intelligent insights, and automated reporting.
Collaborated with data scientists and AI teams on metadata-driven logic generation, data lineage analysis, and embedding enterprise data for GenAI applications.
Monitored and optimized pipeline performance using cloud-native monitoring and logging tools, proactively identifying bottlenecks and improving reliability.
Partnered with cross-functional stakeholders to translate business requirements into scalable data and AI-ready architectures.
Produced comprehensive architecture documentation, data flow diagrams, and operational runbooks, and conducted knowledge-sharing sessions on modern data engineering, cloud platforms, and AI best practices.

Oracle DatabasePython (Programming Language)Data EngineeringAI Enablement

Fidelity investments

Senior ETL Consultant

Mar 2014 – Aug 2016 · 2 yrs 5 mos · Raleigh-Durham-Chapel Hill Area · On-site

Partnered with business stakeholders and analysts to translate complex requirements into scalable data engineering and integration solutions.
Led end-to-end ETL and data integration initiatives, synchronizing and replicating data from Salesforce (SFDC) to Oracle Exadata using Informatica Cloud.
Designed and developed enterprise-grade data pipelines, including source-to-target mappings, transformations, SOQL filters, and business rules for incremental and full data loads.
Engineered and optimized data models and dimensional structures, implementing Slowly Changing Dimensions (SCD Type 1 and Type 2) to support analytics and reporting.
Automated workflow parameterization and incremental load logic, improving pipeline reusability, maintainability, and operational efficiency.
Integrated and managed Salesforce standard objects (Accounts, Contacts, Events, Users, etc.) to enable consistent and reliable downstream data consumption.
Implemented job scheduling and dependency management using AutoSys and JIL scripts, ensuring reliable and timely data processing.
Enforced data engineering best practices including performance tuning, error handling, reprocessing strategies, and naming conventions.
Contributed to Master Data Management (MDM) initiatives, supporting data consistency, governance, and enterprise data quality standards.
Delivered comprehensive technical documentation, testing, and production support, ensuring data accuracy, system stability, and long-term maintainability.

InformaticaPL/SQLData IntegrationETL Development

Quintiles

Principle Engineer

Dec 2008 – Dec 2013 · 5 yrs

Reviewed business and data requirements in Top Team meetings, addressing any ambiguities or discrepancies with the customer.
Thoroughly understood business requirements and mapped them to the Analytix Mapping Manager for clarity and alignment.
Collaborated closely with business leadership to ensure ongoing alignment regarding the development, maintenance, access, security, and retention of global master data.
Worked alongside Business Analysts to review and analyze the QIDE virtual platform Data model.
Extracted data from various sources and loaded it into DFStaging before transferring it to TMODS.
Conducted data extraction from diverse OLTP Systems, including InnTrax, QSIMS, QLIMS, ECG, Salesforce, PeopleSoft Databases, and Siebel CTMS.
Actively participated in team meetings and discussions, proposing solutions to identified issues.
Prepared Software Design documents (SDS), System Manuals, and Runbooks.
Provided system/functional knowledge and technical assistance to team members as needed.
Facilitated weekly status/triage meetings and prepared the Weekly Status Report (WSR), highlighting progress and efforts to the Manager.
Identified business scenarios and generated test data from various source applications for unit testing of the loaded data in the target system.
Developed mappings, Reusable Objects, Transformations, Mapplets, and user-defined functions using a mapping designer, transformation developer, and mapplet designer in Informatica PowerCenter.
Delegated tasks among team members and provided guidance to ensure timely task completion.
Validated data integrity at various levels within the Data Warehouse (DWH) and Delivery Platform, starting from the source data copies through to the end-user feed files.

InformaticaOracleData ManagementData Governance

Oracle

Associate Consultant

Jun 2006 – Dec 2008 · 2 yrs 6 mos

Responsible for gathering business requirements, preparing Source-to-Target Mapping specifications, and defining Transformation rules.
Created Source-to-Target Mapping Specification Documents.
Developed mappings, Reusable Objects, Transformations, and Mapplets using Informatica PowerCenter.
Extracted data from various sources and loaded it into Operational Data Stores (ODS).
Designed and developed complex aggregate, join, and lookup transformation rules to generate consolidated data using Informatica ETL.
Utilized the Update Strategy Transformation to update Target Dimension tables.
Implemented Lookup transformations to retrieve data from source and target tables.
Involved in Performance tuning for sources, targets, mappings, sessions, and server.
Wrote SQL queries and stored procedures to implement business rules and transformations.
Ensured Data Mart loads ran on time and accurately.
Created folders, filters, prompts, and calculations in Framework Manager.
Developed dashboards using Report Studio for management users.
Generated various types of reports including List Reports, Grouped Reports, Cross-tab Reports, Chart Reports, Drill-Down, and Drill-Through Reports.
Developed batch files to automate the execution of workflows and sessions associated with mappings.
Created test cases and conducted unit, integration, and system tests for the Data Warehouse.
Installed, configured, and administered Informatica, creating repositories/folders to support projects.
Set up folders, groups, users, and permissions, performed Repository administration using Repository Manager/Admin console.
Actively participated in team meetings and discussions to propose solutions to problems.