nc.Nithin Chandra Let’s connect ↗

SELECTED WORK / CUSTOMER OUTCOMES

Three problems.
Three working solutions.

Choose a project to inspect the design, contribution and evidence. Start with the overview, then follow the architecture or walkthrough.

SOLUTION ENGINEERING / CONSUMER GOODS

An end-to-end Databricks demo.
A clearer buying decision.

Built a customer-specific demo from SAP ERP ingestion to AI agents. Medallion layers, cashflow and RGM data products, metric views and vector retrieval made the platform vision tangible.

$3.2M+cumulative account services billing
Approach & results

The demo gave stakeholders a working view of the proposed solution, secured buy-in and helped launch the project. An initial $600K engagement expanded into more than $3.2M in account services billing, alongside substantial Databricks consumption. Account billing is a cumulative account result, separate from the GTM team’s 2026 YTD closed-business figure.

DatabricksSAP ERPAgents
Explore the architecture View the project walkthrough View project on GitHub

Synthetic data · runnable source · evidence & walkthrough

RETAIL / GENERATIVE AI

Recommendations that reach the store floor.

Led discovery, PRD and architecture, then built a bounded prototype with real Snowflake data. The Azure application connects vehicle needs with inventory, lead times and comparable products.

600+ storesin the first rollout
Approach & results

I worked with stakeholders and end users to define the consumption experience and validate the prototype with retailers. The engineering team supported production build and deployment. The app helped retailers find inventory, offer comparable alternatives, and identify suitable upsell or cross-sell options.

SnowflakeAzureGenAI
Explore the architecture View the project walkthrough View project on GitHub

Synthetic data · runnable code · decisions & walkthrough

DATA ARCHITECTURE / MANUFACTURING

A shared product foundation across regions.

Primary technical consultant leading design and the project, with hands-on Snowflake and Azure work. Combined business rules, BERT and LLM-based matching to connect regional product identities.

~40% lessduplicate reporting
Approach & results

Connected North America, EMEA and APAC through normalization, candidate blocking, hybrid matching and steward review. The work identified more than $25M in annual savings opportunities across global planning. CoCo, Copilot and Claude supported hands-on development.

SnowflakeAzureEntity resolution
Explore the architecture View the project walkthrough View project on GitHub

Synthetic data · runnable source · evidence & walkthrough