Mukesh Kumar
Mukesh Kumar
Currently
Data Engineer
About
I started my career as a backend engineer, not a data engineer — and for the first couple of years, that felt like the whole plan. I built REST APIs, wired up authentication and role-based access control, designed PostgreSQL schemas, and automated business workflows that other teams depended on daily.
Somewhere along the way, I noticed a pattern: the parts of every project I cared about most weren't the endpoints themselves, but the data moving through them — how it was validated, structured, and made trustworthy before anything downstream could rely on it. That noticing turned into curiosity, and curiosity turned into deliberately building things: cleaning pipelines, incremental loaders, analytics tables designed to be queried, not just stored.
I'm not calling myself an aspiring data engineer. I have 3 years of professional software engineering experience, and I'm transitioning into data engineering through production-grade projects, not tutorials — starting with TaskPulse, an ETL platform built the way I'd build it at work. I'm still learning — the cloud platforms below are a work in progress — but the engineering fundamentals underneath all of it aren't new to me.
3+
Years of Experience
2
Companies
1
Production ETL Project
Backend → Data
Current Focus
Featured Project
A layered ETL platform turning simulated task-management activity into analytics-ready insights.
TaskPulse is built around a question every engineering manager eventually asks: which users are productive, which workspaces are falling behind, and where are tasks piling up? Answering that by querying a live operational database directly is a bad idea — it competes with production traffic and invites ad-hoc, unrepeatable analysis. TaskPulse solves it by generating realistic workspace activity (tasks, assignments, status changes) and running it through a layered pipeline — raw capture, cleaning, and analytics — so the numbers a dashboard would show come from a purpose-built, incrementally-updated store instead of a query bolted onto the live app.
Event Generator
Raw Database
Python ETL
Clean + Analytics DBs
Dashboard
3
Databases
7
Pipeline Modules
Incremental
Load Mode
Dockerized
Deployment
My Journey
Three years of shipping backend systems, now extending into data engineering.
Feb 2023 — Feb 2025
Mar 2025 — Feb 2026
Present
Tech Stack
Organized by what I can build with it, not just what I know.
Data Ingestion
Data Cleaning
ETL
Analytics
Backend
Cloud
DevOps
Why Data Engineering
I didn't start out planning to become a data engineer. I started as a backend engineer — building REST APIs, designing database schemas, wiring up authentication and role-based access control. Somewhere in the middle of that work, I noticed the parts I liked most weren't the endpoints themselves, but the data flowing through them: how it was modeled, validated, and shaped before anything else could use it reliably.
Reliability
Backend systems taught me that uptime and predictability aren't optional — the same standard applies to a pipeline that a dashboard depends on every morning.
Scalability
Designing APIs to handle growing load maps directly onto designing pipelines that handle growing data volume without a rewrite.
API Design
A well-designed API has clear contracts and predictable failure modes — a well-designed pipeline needs exactly the same discipline at each stage.
Database Design
Years of schema design and query optimization translate directly into modeling analytics tables that are fast to query and easy to reason about.
Clean Architecture
Separating concerns in a backend service is the same instinct as separating raw, cleaned, and analytics-ready data into distinct layers.
That overlap is why the shift into data engineering has felt less like starting over and more like pointing existing skills at a new problem. TaskPulse was the first project where I built that belief into something real — production-style, not a tutorial.
Why Hire Me
Three years of production backend experience means I ramp on data systems faster than someone starting from zero.
Production Mindset
Ships containerized, version-controlled systems designed to run reliably, not just work once.
Strong Backend Foundation
3 years building production REST APIs, authentication, and RBAC systems used by real users.
Database Expertise
Hands-on schema design and query optimization across PostgreSQL and MongoDB.
Modern ETL Development
Built a full incremental ETL pipeline from raw data to analytics-ready tables — not just tutorials.
Problem-Solving
Comfortable translating ambiguous business processes into working, automated systems.
Continuous Learning
Actively building cloud and data platform depth through certifications and production-style projects.
Ownership
Takes projects from problem definition through architecture, implementation, and documentation.
Contact
Open to Data Engineer and backend roles where I can keep building production data systems. I usually reply within a day or two.
Chennai, Tamil Nadu, India