Semantic layer
Define measures, dimensions, grain and relationships so tools share the same business meaning.
SNOWFLAKE SEMANTIC VIEWS · UNITY CATALOG METRIC VIEWS · APACHE OSSIEChicago, IL / Solutions Architect
Data & AI
architecture.
Built for business.
I’m Nithin, a Solutions Architect designing data and AI systems around the customer’s problem. My AI foundation spans 8+ years, from traditional ML and neural networks to today’s GenAI systems. Semantic and context layers are a key specialty. I stay hands-on from discovery through delivery.
Pick a rabbit hole.
Builder. DJ.
Always curious.
Always curious.
Engagement Manager
MathCoStrategy meets
hands-on engineering.
MathCoStrategy meets
hands-on engineering.
SELECTED IMPACT
Work with
measurable outcomes.
600+
Retail stores reached by
a GenAI recommendation app
$3.91M
2026 YTD closed business
GTM team I lead & orchestrate
~$7.2M
Current active pipeline
GTM team · as of Oct 2026
SPECIALIZATION / CONTEXT & SEMANTIC LAYERS
Shared meaning.
Relevant context.
I launched a Context & Semantic Layer offering and built reusable accelerators that turn business definitions, data relationships and policies into a foundation for analytics and AI.
I built a Spanner Graph prototype connecting Merchandising and Customer domains to explore renewal-associated pantry products across demographic cohorts. My showcases and proposals span Snowflake, Databricks and GCP.
Built acceleratorsLed platform demosDesigned enterprise semantics
Context layer
Connect entities and metrics to their sources, derivation, owners and policies. Expose relevant context through bounded agent tools.
SPANNER GRAPH · NEO4J · OKF · MCP
Trusted data→Business definitions+Context relationships→Governed tools & answers
4 pursuitsContext & Semantic Layer offering
~$1.4Moffering pipeline
4 domainsenterprise semantic architecture
Earlier offering snapshot · subset of the GTM team pipeline · Finance, Merchandising, Supply Chain and Store Operations
01 / SELECTED WORK
Built around the
customer’s problem.
A few examples across retail AI,
data architecture, and
technical selling.
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.
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.
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.
Synthetic data · runnable source · evidence & walkthrough
ALSO IN THE MIX
Snowflake partner co-sell · Dealer loyalty & promotion ROI · Demand forecasting
SOLUTION ARCHITECTURE / TECHNICAL DEEP DIVES
The complete system.
The choices behind it.
End-to-end architectures, data contracts,
runtime sequences and
operating patterns.
01 / DATABRICKS + BUSINESS SEMANTICS
Beauty data & AI demo
SAP integration, medallion products, semantic metrics and identity-aware agent tools.
Inspect the full architecture
02 / SNOWFLAKE + AZURE
Retail recommendations
Data integration, inventory-aware decisioning and the retailer application runtime.
Inspect the full architecture
03 / HARMONIZATION + STEWARDSHIP
Global product master
Regional SAP, entity resolution, steward feedback and governed global publishing.
Inspect the full architecture02 / ABOUT ME
Comfortable with
the business and the build.
I connect customer requirements to system design and stay hands-on through the build.
I work with executives, account teams and engineers to define the problem, choose the right data and AI approach, and validate it through working prototypes. My work connects data platforms, models, application experiences and business outcomes across retail, consumer goods, manufacturing, healthcare and supply chain.
I’ve benchmarked and deployed traditional ML and neural-network models since 2018. At Mu Sigma, I deployed ML and data engineering pipelines on GCP with Jenkins. At Staples, I built SARIMAX and XGBoost forecasting models and benchmarked neural approaches including N-BEATS and N-HiTS. That grounding in statistics, machine learning and neural networks informs my GenAI and agent architecture work today.
At MathCo, I lead and orchestrate engineering GTM pursuits, bringing in domain experts, specialist architects, delivery and customer success while staying hands-on with demos, custom prototypes and architecture on Snowflake, Databricks and GCP. Earlier, I built analytics and data products at Staples and helped grow a retail engagement at Mu Sigma.
BEYOND WORK
Off the clock.
Still curious.
Music, pickup games,
and street photography.
Good music. Long mixes.
House and techno are my go-to sounds. I enjoy DJing and sharing music on SoundCloud.
Listen to my mixes ↓Listen on SoundCloudAlways up for a pickup game.
I play basketball and volleyball for fun, and I’m always up for a pickup game.
Got a game? Count me in
a few frames ↘
A camera in my pocket.
I’m exploring street photography with my iPhone 17 Pro, with a dedicated camera on the wish list.
Take a little photo walkON THE DECKS / HOUSE & TECHNO
DJ ENCEEA different kind of flow.
A few mixes from my SoundCloud. Press play and stay a while.
Open my SoundCloud profileChoose a mix and press play.
PERSONAL WORK / PHOTOGRAPHY
The city has a rhythm.
I stop for the details.
A little light, a good line, a street worth stopping for. A
selection of my photographs.
Take the scenic route.
03 / SKILL SET
What I bring
to the table.
Technical depth, commercial context,
and experience getting
things delivered.
01
Solutions architect
Stakeholder discovery, requirements and PRDs, system design, cloud and data architecture, technical prototypes, executive presentations and delivery planning.
02
Data engineering & platforms
SQL, Python, Snowflake, Azure, Databricks and GCP. ETL/ELT, entity resolution, master data and ML/data pipeline deployment.
03
Machine learning & AI
8+ years of AI/ML experience. Traditional ML and neural-network benchmarking and deployment since 2018. SARIMAX, XGBoost, N-BEATS and N-HiTS forecasting; optimization, GenAI and agents.
04
Context & semantic architecture
Snowflake Semantic Views, Unity Catalog metric views, business grain and relationships, knowledge graphs, Spanner Graph, Neo4j, OKF, Apache Ossie, context engineering and bounded MCP interfaces.
05
AI-assisted development
Frequent hands-on use of Claude Code, Codex, and Cursor, with Genie Code and Snowflake CoCo for cloud development.
PARTNER CERTIFICATIONS
Snowflake Partner: Gen AI · Databricks Partner: Gen AI & LLM
04 / EXPERIENCE
The path
so far.
JAN 2025 to PRESENTCURRENT
MathCo
Engagement Manager, Engineering GTM & Solutioning Sep 2025 to Present
Senior Consultant, Client Delivery Jan to Sep 2025
Lead and orchestrate engineering GTM pursuits, with team results of $3.91M closed in 2026 YTD and approximately $7.2M current pipeline. Personally advance opportunities through discovery, showcases, architecture presentations and custom prototypes on Snowflake, Databricks and GCP.
Bring in domain SMEs and specialist architects for deep dives, delivery teams for implementation and customer success leads for engagement. Launched a Context & Semantic Layer offering and built reusable accelerators.
SEP 2023 to JAN 2025
Staples
Data Scientist
Built forecasting, optimization, and data pipelines for inventory and fulfillment, plus GenAI solutions on Snowflake and Azure.
Earlier co-op: Jun 2022 to Jan 2023
DEC 2021 to SEP 2023
Northeastern University ITS
Program Lead, Customer Experience
Improved service response times through analysis of 100K+ tickets and mentored 80+ student technicians while completing my master’s.
JUN 2018 to AUG 2021
Mu Sigma
Decision Scientist
Led retail analytics, built proposals and customer demos, and pursued account expansion. Deployed ML and data engineering pipelines on GCP with Jenkins and measured 400+ store pilots.
05 / GET IN TOUCH
Have a data or AI
challenge in mind?
Let’s talk about the problem and what we could build.
nithinchandra357@gmail.com