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Ayan Putatunda
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Ayan Putatunda

Staff Data Engineer. Data platforms for AI, and the agentic systems on top of them.

Pleasanton, CA · ayanputatunda87@gmail.com · ayanputatunda.com · linkedin.com/in/ayanputatunda · github.com/AyanPutatunda

Summary

Staff Data Engineer and IEEE Senior Member working on petabyte-scale data platforms for production AI. Currently leads AI-readiness for the Zendesk Data Platform: context governance, Model Context Protocol architectures that let agents consume governed enterprise data, and agentic workflows that automate the analytics-engineering lifecycle end to end with a human at every review gate. Keynote at IEEE AIC 2026 and session at dbt Summit 2026; co-presented at Snowflake World Tour Chicago in October 2026 at Snowflake's invitation. Co-author of a vision paper under review at the AAI-BD 2026 workshop, IEEE BigData 2026. Personal projects at Axiomic AI, an experimental, non-revenue playground for new technology and deployment, include three live sites: PersonasFlow, EstateVision, and WealthPilot.

Core skills

Agentic AI
Anthropic Claude API, Claude Code, Claude Agent SDK, MCP, LangGraph, Multi-agent systems, RAG and vector search, LLM evaluation
Data platform
Snowflake, Snowflake Cortex, dbt, Airflow, Fivetran, BigQuery, Spark, Kimball modelling, Semantic layers
Languages and cloud
Python, SQL, Docker, GitHub Actions, GCP, Snowflake Data Cloud
Leadership
Technical mentoring, Team building, Stakeholder management, Engineering best practices

Experience

Staff Data EngineerNov 2024 – present
Zendesk, San Francisco
  • Leads AI-readiness work for the Zendesk Data Platform: Snowflake Cortex semantic layers and skills-driven agentic data engineering.
  • Architected petabyte-scale infrastructure with Fivetran, Airflow, and dbt; 40% better delivery efficiency at 99.9% uptime across 5+ engineering teams.
  • Established engineering best practices; mentors engineers on multi-system, long-term projects.
Staff Data EngineerMay 2022 – Nov 2024
Achieve (formerly Freedom Financial Network), San Mateo
  • Led the FDR Sales Data Transformation on Google Cloud: 500K+ unified customer profiles in a BigQuery data lake.
  • Batch and streaming ETL frameworks reduced data inconsistencies by 60%.
Engineering Manager, Principal Data Engineer, Senior Data EngineerSep 2019 – Apr 2022
Noodle.ai, Palo Alto and San Francisco
  • Architected the pipeline for a first-in-class supply chain AI platform; TB-scale, 99.9% uptime.
  • Built and scaled the data engineering team from 2 to 8 with 100% retention.
  • Configurable models and a reusable Airflow framework: implementation time down 50%, development up 60%.
Team Lead, Associate Projects, Senior Developer, Programmer AnalystOct 2010 – Sep 2019
Cognizant, Kolkata / Buenos Aires / San Francisco
  • Multi-channel retail POS data integration (RAYMARK, MSBI, SQL Server) for global retail clients; 99.5% data accuracy with fault-tolerant ETL.
  • Automated reconciliation processes eliminated manual validation and reduced errors by 85%.

Selected work

Skills-driven agentic data engineering2025–2026
Zendesk Data Platform
  • A governed library of AI skills and sub-agents that automates the analytics-engineering lifecycle across multi-repo dbt and ingestion workflows, with humans in the loop.
  • Roughly 2.5× faster time-to-production for analytics work, as presented at dbt Summit 2026.
  • Targeting an 80% reduction in manual pipeline development across multi-repository dbt and ingestion workflows.
Autonomous incident response agent2025
Zendesk Data Platform
  • Zero-touch detection, root-cause analysis, and auto-remediation of data pipeline failures using the Claude Agent SDK with Snowflake, dbt, and GitHub MCP servers.
  • Targeting a 70% reduction in mean time to resolution for pipeline incidents.
  • On-call load shifted from log reading to reviewing a proposed fix.
Semantic layer on Snowflake2025–2026
Zendesk Data Platform
  • A unified business vocabulary across 10+ domains, built with dbt metrics and Snowflake Cortex semantic views, so people and agents ask questions in the same words and get the same answer.
  • Ad-hoc query requests down 45%.
  • Self-serve analytics opened to non-technical stakeholders.
contextctl: auditable context infrastructure for AI agents2026
Research
  • A vision paper and open-source prototype arguing that agent context should be governed data infrastructure: open files for truth, Git for time, a hash-named evidence folder, one SQLite sidecar for speed, and a token-budgeted serving protocol. Under review at the AAI-BD 2026 workshop, IEEE BigData 2026; decision expected Nov 12.
  • Vision paper submitted Oct 26, 2026 to the 1st IEEE Big Data Workshop on Agentic AI for Big Data (AAI-BD 2026), IEEE BigData 2026. Under review; decision expected November 12, 2026.
  • Measured feasibility of the primitives: snapshot commit 155 ms and full sidecar rebuild 0.47 s at 10,000 concepts; point-in-time reads and reverts around 3 to 5 ms; 28 MB total storage.
Axiomic AI agent harness2025–2026
Open source, personal R&D
  • The multi-agent repository template every Axiomic AI product is built from: agent prompts, MCP server configs, CI, and deploy wiring. Fork, describe the domain, ship.
  • PersonasFlow, EstateVision, and WealthPilot all run on it; each new product started from the same fork.
  • Within Axiomic AI, a personal and non-revenue playground, the harness takes the place of an engineering team.

Research and publications

  • Vision Paper: contextctl — Auditable, Open-Source Context Infrastructure for AI Agents. 1st IEEE Big Data Workshop on Agentic AI for Big Data (AAI-BD 2026), IEEE BigData 2026. Submitted Oct 26, 2026. Under review, decision expected November 12, 2026.
  • Essential PySpark for Scalable Data Analytics. Technical reviewer. Packt Publishing, ISBN 978-1-800563094. Published

Speaking

  • Panel, USF Enterprise AI Summit, University of San Francisco, Oct 30, 2026. Step Inside the AI-Powered Enterprises.
  • Session, Applied AI Summit, Oct 13–15, 2026. Making a Data Platform AI-Ready.
  • Session and discussion, Snowflake World Tour, Chicago, Oct 5, 2026. What's New: Zero to a Trusted Semantic Layer in Snowflake, with Aniruth Narayanan, Snowflake.
  • Session, dbt Summit 2026, Las Vegas, Sep 15–18, 2026. AI-Powered Data Development: How Agentic SDLC & dbt-MCP Transformed Our Data Engineering Workflow.
  • Keynote, IEEE 5th World Conference on Applied Intelligence and Computing (AIC 2026), Aug 29, 2026. Unlocking Intelligence through Data.
  • Address, University of San Francisco. Guest address to the graduating class, MS in Data Science & AI.
  • Podcast, #idataengineer podcast, Feb 5, 2021. Data Engineering Confessions #9.

Community

  • Judge, Cal Hacks 13.0. UC Berkeley. Palace of Fine Arts, San Francisco, Oct 23–25, 2026.
  • Judge, 2nd NextGen Hackathon 2026. ACM Fremont Chapter with the Soft Computing Research Society, Aug 15–16, 2026.
  • Mentor, Junior and mid-level engineers moving into data and AI engineering, US and Singapore. 20–30 professionals mentored across enterprises; public live sessions on YouTube, Ongoing.
  • IEEE, senior member. Member of the Computer Society, Technology and Engineering Management Society and Young Professionals.

Personal projects

  • Axiomic AI (axiomic-ai.com). Ayan's experimental, non-revenue playground for trying out new technology and deployment: one agent harness, three live personal projects.
  • PersonasFlow (personasflow.com), live. Life-management platform: intelligent daily routines, persona management, and progress tracking across every role a user plays.
  • EstateVision (estatevision.io), live. Rental portfolio management for property owners: portfolio tracking, centralized document store, automated rent-reminder notifications.
  • WealthPilot (pilotmywealth.com), live. AI-driven personal finance: monthly investment amounts and allocations personalized to risk tolerance and financial goals.

Teaching

  • Built from Bits (YouTube @ayan-in-tech). Hands-on data and AI tutorials: Claude Code, MCP, agents, dbt, Snowflake. Also on Substack and Medium.
  • The Practitioners Pod (YouTube @thepractitionerspod, thepractitionerspod.com). Conversations with people who ship data and AI systems for a living.
  • Built from Bits (builtfrombits.com), learning platform. Live.

Education

  • Master of Computer Science in Data Science, University of Illinois Urbana-Champaign
  • B.Tech in Computer Science and Engineering, West Bengal Institute of Technology