Jayaram Venkataraman

Digital-first IT services firm specializing in AI/ML, cloud engineering, and data analytics for healthcare, finance, and life sciences.

• —Generated $900K in annual business value by refactoring 500+ data models and pipelines (Spark and dbt) for parallel execution; reduced annual infrastructure spend by $217K and improved pipeline efficiency by 272%, significantly decreasing latency for downstream stakeholders. Main operational improvement was led by AI-enabled bottleneck detection and planning.
• —Designed and delivered enterprise architecture solutions and disaster recovery specifications across Data and AI in Snowflake and Azure, helping drive projects impacting $3.8M in medium-term revenue across data engineering, ML, and operations programs.
• —Translated requirements into robust data frameworks supporting analytics and decision-making with scalable data designs and POCs in a FinOps data architecture team. Coordinated resource management and requirements alignment across the data practice.

Healthcare spin-off from 3M delivering med-tech innovations in wound care, health IT, and surgical products through data-driven technologies.

• —Reduced monthly operational costs from $252K to $18K (93% reduction) across 7 analytics systems while improving ticket resolution by 39% using Lean IT and introducing operating design principles such as capacity planning within Agile.
• —Led cloud migration from Cloudera to AWS and Snowflake, directing a team of 8 and coordinating across 4 business and technology teams; managed technical design documents, stakeholder alignment, ML models and pipelines. Also utilized GCP and Azure to cut costs and dependency as FinOps architect and lead.
• —Implemented AI Agents to analyze, assign, and log tasks in JIRA for automated SQL/data-ops monitoring using LangChain, increasing operational efficiency by ~40% with cost reductions of 8%.
• —Managed >$3.25M in annual system budgets across 8 platforms; maintained vendor relationships with Snowflake, Oracle, and AWS. Trained team members in modern data stack best practices and handled vendor optimization strategy.

Data engineering and digital transformation firm delivering cloud-native platforms, AI solutions, and managed services with AWS, GCP, Azure, and Oracle Cloud.

• —Partnered with delivery manager to stand up data engineering and science practice; grew practice revenue from 1% to 21% of total company revenue ($6.82M) by 2021 through cloud data engineering migrations and ML implementations across AWS, Azure, and GCP.
• —Envisioned and executed 2nd global Oracle SIA implementation, enabling 4x faster client value realization and 70% defect reduction across education and manufacturing sectors.
• —Created cross-product data platform leveraging IP across 18 products, generating $1.79M in cost savings.
• —Designed hybrid incremental ETL methodology for Oracle BI Apps, enabling ~$2.1M in consolidated revenue across 4 programs. Delivered 21 projects with a defect count under 35 by applying reusability.

Global IT leader delivering consulting, cloud, AI, and digital transformation at enterprise scale across banking, retail, and manufacturing.

• —Technical lead for enterprise finance, supply chain, and HR analytics implementations across India and UK using the Oracle BI ecosystem.
• —Constructed data lineages and set up Oracle BI Apps end-to-end to technical standards, delivering ~£1.2M in annual client value.

Global technology company delivering engineering, cloud, and AI services with deep expertise in product engineering and IT infrastructure.

• —Delivered PL/SQL database scripting, C# application development, and BI solutions for Fortune 500 financial institution (an Australian bank).
• —Developed ODI interfaces and built XML-based document generation tool in C#.NET and PL/SQL contributing to $4.2M in validated revenue improvements over 10 years (valued at 10% discount) to wealth banking.