Building scalableSaaS platforms whereengineering excellencemeets business impact.
Founder · CEO
SKATTECH IT Services
I'm Nadimuthu Sarangapani — a CEO and Senior Software Engineer with 13+ years architecting platforms across EdTech, Construction 3D, E-Commerce, and Job Portal verticals. Trusted by founders, CTOs, and boards to turn complex ideas into high-impact, scalable products.
Focus:
01 — Profile
I build thesystems thatbecome thebusiness.
Thirteen years ago I shipped my first product to a paying customer. Since then I've spent every working hour on a single conviction: software is the highest-leverage asset a company will ever own — and most teams build it like it isn't.
I've built the full surface of modern SaaS — web, mobile, infrastructure, data, and the AI systems now reshaping all three. As a founder I've sat in the seat where every decision is a trade between speed, scale, and survival. That seat changes how you write code, hire engineers, and price a product.
Today I lead SKATTECH IT Services and advise a small set of founders and boards on the bets that matter — re-platforming, applied AI, enterprise readiness, and the org design required to ship any of it. I don't deliver decks. I deliver shipped systems and the team that owns them.
01
Engineer first.
I still write production code. Strategy without technical fluency is theater — leverage comes from understanding the system at every layer.
02
Architect for compounding.
Every system I build is designed to outlive its first assumptions. Scalable, secure, observable — so the next decision is cheaper than the last.
03
Operate like an owner.
Engineering decisions are capital allocation decisions. I optimize for the outcome on the P&L, not the elegance of the diagram.
Years building
13+
Companies founded
2
Engineers led
80+
Production stacks
Web · Mobile · AI
02 — What I do
Five pillars wheretechnical depth becomescommercial leverage.
Every engagement maps to one of these disciplines. Each one engineered to move a number that ends up in front of your board.
SaaS Architecture & Platform Engineering
throughput gains
Platforms engineered to scale revenue, not headcount. Cloud spend down, throughput up, on-call quiet.
Full-Stack Web & Mobile Development
yrs in production
Product surfaces customers actually use. Faster ship cadence, lower defect rate, retention that compounds.
Data Engineering & Analytics
decision systems
Decision systems that turn raw events into board-ready truth — and into product features that pay back.
Marketing & Sales Technology
CAC reduction
GTM tech that compounds. CAC down, conversion up, every dollar of pipeline measured to source.
Product Strategy & Revenue Enablement
SaaS to Series B
Strategy that ships. I bridge product, engineering, and revenue so the roadmap moves the P&L.
03 — Technical expertise
Deep engineeringacross the modernSaaS topology.
Five capabilities I've shipped to production at scale. Each one chosen because it shows up in the architecture decisions that decide whether a SaaS company compounds — or stalls.
MERN / MEAN Stack
End-to-end JavaScript expertise across MongoDB, Express, React/Angular, Node — production-grade, type-safe, and battle-tested.
Microservices Architecture
Domain-driven, event-sourced services with clear contracts. Independently deployable, observable, and resilient under load.
Micro Frontends (MFEs)
Vertical slices owned by independent teams. Module Federation and contract-first composition that ship on independent cadences.
Cloud-Native SaaS
Twelve-factor, container-orchestrated platforms built for elasticity. IaC from day one, shipped via progressive delivery.
Multi-Tenant Architecture
Isolation models that match the buyer — pooled, siloed, or hybrid. Row-level security, per-tenant observability, zero blast radius.
Engineered for —
Scalability. Performance.
Security. Maintainability.
The four properties every line of code is reviewed against.
Scalability
Horizontally elastic from day one. Designed for the load you'll have, not the load you have.
10M+ rps
Performance
P99 budgets enforced at the edge. Latency is a feature — and it's measured continuously.
< 80ms P99
Security
Zero-trust by default. SOC 2, HIPAA, ISO 27001. Threat models live alongside the code.
SOC 2 · HIPAA
Maintainability
Code reviewed for the engineer who inherits it. Tests, types, and docs as first-class citizens.
> 85% coverage
04 — Data & performance
Where millisecondsbecome margin.
Query plans, index strategy, and warehouse economics — engineered against the workload, measured against the bill. Tuned for systems that have outgrown the default playbook.
P95 query latency
Pricing API · Aurora MySQL
Warehouse spend
BigQuery · 14B rows/day
ORM hotspots removed
Node · Prisma audit
Throughput uplift
Reporting · post-index
Advanced SQL Optimization
Plan-driven tuning. I read EXPLAIN ANALYZE the way a trader reads a tape — and I rewrite the query, not the symptom.
Schema Design & Indexing
Normalized where it earns its keep, denormalized where reads dominate. Composite, covering, and partial indexes engineered to the access pattern.
Query Refactoring & ORM Optimization
N+1 eliminated at the boundary. Hot paths moved to typed SQL, dataloaders, and prepared statements — without surrendering developer ergonomics.
MySQL & BigQuery at Scale
From InnoDB tuning and replica routing to BigQuery slot economics, partitioning, and clustering — chosen for the workload, not the brochure.
Cost-Efficient Data Systems
Compute and storage modeled like a P&L line. Materializations, tiering, and incremental models that bend the curve before it bends the budget.
-- Partition: event_date · Cluster: tenant_id, event_name
CREATE TABLE analytics.events
PARTITION BY event_date
CLUSTER BY tenant_id, event_name AS
SELECT * FROM raw.events;
-- Slot-aware aggregate, no SELECT *
WITH windowed AS (
SELECT
tenant_id,
DATE_TRUNC(event_date, WEEK) AS wk,
COUNTIF(event_name = 'checkout.completed') AS conversions,
APPROX_QUANTILES(latency_ms, 100)[OFFSET(99)] AS p99_ms
FROM `analytics.events`
WHERE event_date BETWEEN DATE_SUB(CURRENT_DATE(), INTERVAL 28 DAY)
AND CURRENT_DATE()
AND tenant_id IN UNNEST(@tenants)
GROUP BY tenant_id, wk
)
SELECT * FROM windowed
QUALIFY ROW_NUMBER() OVER (PARTITION BY tenant_id ORDER BY wk DESC) <= 4;Stack ledger
Tools chosen for the workload — not the brochure.
05 — Integration & data engineering5+ yrs
Data plumbed forthe decisionsthat matter.
Five years architecting the integration layer between operational systems, the warehouse, and the surfaces that turn raw events into product, marketing, and executive judgment.
SnapLogic ETL
Enterprise integration patterns at scale — pipelines, snaps, and ultra tasks orchestrated with governance, lineage, and SLA-grade reliability.
Segment CDP
Customer data engineered as a product. Tracking plans, Protocols, and reverse-ETL that keep behavioral truth synchronized across the stack.
Data Warehousing
Modeled warehouses that survive the org chart. Medallion layering, slowly-changing dimensions, and contracts between producers and consumers.
Event-Driven Architectures
Kafka, Kinesis, Pub/Sub — schemas registered, replayable, and idempotent. Real-time fabric that decouples teams without losing the audit trail.
Analytics & BI Workflows
Semantic layers and metric stores that make a single number defensible across product, finance, and the boardroom.
Operating principle
Pipelines are products.
Treat them that way.
Versioned schemas. Owned SLAs. Lineage end-to-end. Anything less is technical debt with a dashboard.
↳ Where the data lands
Three audiences. Three operating cadences. One disciplined data model.
Product decisions
Behavioral truth wired directly into the roadmap. Activation, retention, and cohort signal that retires the loudest opinion in the room.
Marketing strategy
Attribution that survives auditing. Channel mix, MMM, and lifecycle automation that move CAC and LTV in the same direction.
Leadership insights
One source of truth for the operating cadence. Board metrics, forecast accuracy, and unit economics defensible to the cap table.
06 — CEO & Founder
Technology as arevenue line item —owned end-to-end.
Sitting in the founder seat changes how you build. Every system I own is instrumented to a number on the P&L — and engineered to keep moving it long after the launch deck is filed.
Product Strategy
Roadmap as capital allocation. Bets sized to market reality, sequenced for compounding outcomes — not feature theater.
SaaS Architecture
The technical bet is the business bet. Multi-tenant, observable, and engineered to scale without re-platforming the company every two years.
Marketing Technology
MarTech as a product surface. Attribution that survives audit, lifecycle automation that compounds, and a single behavioral truth across the funnel.
Sales Enablement Systems
RevOps wired to the product. CRM, signals, and orchestration that turn pipeline into a measured, repeatable process — not folklore.
↳ Systems shipped under this seat
Revenue surfaces, engineered like product.
Each one designed to be measured, iterated, and held to a number — quarter after quarter.
System
Referral Systems
Engineered, not bolted on.
Double-sided incentives, fraud guardrails, and on-brand share surfaces. Wired to billing and the warehouse so attribution is bullet-proof.
Outcome
23% of new ARR · self-served
System
CRM Integrations
One contract per object.
Salesforce / HubSpot wired to product, billing, and the data warehouse with versioned schemas — so reps see the same truth as the boardroom.
Outcome
Forecast accuracy ±3%
System
Analytics-Driven Campaigns
Measured before launch.
Hypotheses with pre-registered metrics, holdout cohorts, and lifts attributable past last-click. Marketing operated like an engineering team.
Outcome
CAC −38% · LTV:CAC 4.2x
System
Monetization & Growth Workflows
Pricing as a product.
Usage-based billing, paywall experiments, and expansion loops engineered into the platform — not retrofitted at the QBR.
Outcome
NDR 132% · expansion engine
Operating thesis
"If a system can't be tied to a number on the income statement, it isn't shipped — it's decoration."
NDR
132%
CAC payback
9 mo
Self-served ARR
23%
Forecast accuracy
±3%
07 — Expertise matrix
Nine disciplines.
One operating system
for shipping SaaS.
A single map of where I operate — from the code path to the cap table. Built over 13 years, refined under real revenue.
Full-Stack Web & Mobile
Product surfaces customers actually use.
MERN / MEAN
End-to-end JavaScript, type-safe.
Microservices & MFEs
Independently shippable, contract-first.
SaaS & Multi-Tenant
Pooled, siloed, hybrid — by buyer.
SQL & Performance
Plan-driven, P99 budgeted.
MySQL · BigQuery · ORM
Workload-fit, cost-modeled.
SnapLogic · Segment · DWH
Pipelines as products.
Marketing & Sales Tech
Attribution that survives audit.
Startup & Enterprise Leadership
Founding engineer to 80+ org.
03 — Impact
Numbers that survivedthe boardroom.
Years compounding deep system expertise
Engineers led across orgs and continents
SaaS products taken through Series B
04 — Selected work
A decade ofconsequential systems.
Full-stack EdTech learning management platform
Founder & Architect
Real-time 3D construction visualisation & BIM portal
Lead Engineer
Scalable multi-vendor e-commerce marketplace
CTO Consultant
AI-powered job portal & talent matching engine
Senior Software Engineer
Let’s buildscalable systemsthat move theP&L.
Founders, CTOs, and boards bring me in when the technical bet is the business bet. If that's the room you're in — let's talk.
↳ Modes of engagement
select one — or compose
SaaS Consulting
Architecture reviews, re-platforming, and the build-vs-buy calls that compound for years.
Project · 4–12 wks
CTO / Architecture Advisory
Fractional executive judgment for founders and boards navigating the next inflection.
Retainer · monthly
Strategic Partnerships
Co-building category-defining products with operators who move at executive speed.
Selective · equity
Engineering Leadership
Org design, hiring, and operating cadence for teams scaling past their first ceiling.
Embedded · quarterly
Direct line
nadimuthu.s@skattech.comReplies within one business day. Discovery calls capped at 30 minutes — both of ours are valuable.
Based
Chennai, India
Timezone
IST · flexible
Response
< 24 hours
Engagements
2 active slots
Book a call
Start the conversation.
Share a few details and I'll follow up within one business day to schedule a discovery call.