Deenu Gengiti
Engineering Manager, Data Governance & Analytics @Emerson
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WORK HISTORY
Engineering Manager, Data Governance & Analytics @Emerson
Toronto, ON, CA
Leading the AI and data engineering practice;Architect enterprise-wide data governance strategy and analytics transformation, championing modernized data engineering and scalable cloud infrastructure to unlock business valueSpearhead AI Center of Excellence with executive sponsorship, driving end-to-end ML lifecycle from use case discovery through production deployment, delivering measurable business impact across core operations
EDUCATION
University of California, Berkeley, Haas School of Business
Data Strategy: Leveraging Data as Competitive Advantage
Stanford University
Artificial Intelligence (AI) Product Management (BUS 261), Artificial Intelligence, Blue Ocean Strategy, Design Thinking, Agile AI Product Lifecycle
Queen's University
Master's degree, Management in Artificial Intelligence
University of Toronto
Coding - Fullstack Development
York University
Graduated in Advanced Data Science, Predictive Analytics and Big Data
Lassonde School of Engineering - York University
Certificate in Technology Entrepreneurship (BEST)
York University
Bachelor of Science - BS, Computer Science (Honours)
SKILLS
ABOUT DEENU GENGITI
An IT professional with extensive experience over 22 years in Engineering Systems (PLM), AI Engineering, and Data Engineering. Specializing in platform engineering, XOps (DataOps, DevOps, MLOps and LLMOps), I focus on developing scalable, data-driven solutions. I am passionate about research and innovation, I continuously learn new technologies to tackle complex challenges.Highlights: 20••••24: Leading the strategic role as Data Governance and Analytics leader Leading AI Center of Excellence for vision, strategy, and execution of responsible AI to drive innovation Leading AI Governance initiatives for compliant & safe deployment of ML & LLM models Advocating for modernization to a cloud-native stack, developing scalable apps on OpenShift/Kubernetes. Successfully transitioned from traditional data warehouse products to a modern stack i.e. distributed, scalable, and cloud-native architecture (ArangoDB, Apache Kafka, Airflow, Spark, React Js) Modernized ETL pipelines to handle 200+ million records from various ERPs, using batch and real-time streaming. Coaching and guiding data engineers and analytics teams in leveraging knowledge graphs and graph algorithms Leading MLOps/DataOps/DevOps strategy and building Data and API platforms with Azure RedHat OpenShift. Promoting frontend development with capabilities like click-stream analytics, vector searh, full-text search, etc Building and managing global teams for Data Engineering, Data Analytics, and Data Science capabilities Defining and executing Data Governance strategies, ensuring data quality, and complianceFocus areas: Strategy, Governance, Language Models (LLMs), Deep Learning, Personalization and Search, Recommender Systems, Graph Neural Networks, Classical Machine Learning,
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