Nitesh Kumar  ·  Senior AWS Data Engineer  ·  4.3+ yrs

Mid-Level
India4.3+ years experienceremote
Available within 48 hrs

About Nitesh

Nitesh Kumar has developed and optimized ETL pipelines for diverse data sources and destinations, including cloud-based data warehouses. He has proven experience with unstructured data extraction and has built and deployed scheduled and event-triggered data pipelines using AWS Glue and Airflow. His expertise includes data quality assurance and providing end-user support, making him a valuable asset in data engineering roles.

Core expertise

Python
language
10/10
AWS
cloud
9/10
SQ
SQL
language
9/10
AG
AWS Glue
devops
9/10
AR
AWS Redshift
database
9/10
AI
Airflow
devops
8/10
React
frontend
8/10

Additional skills(12)

PythonReactPostgreSQLAWS GlueAWS RedshiftAWS TextractSQLS3AirflowAWS Lambda

Why hire Nitesh?

Production deploy authorityBuilt from scratch data solutionsManaged end-to-end data ingestion

Expertise in AWS services for data warehousing and ETL pipeline development.

Proficient in Python and SQL, utilized across multiple data engineering projects.

Developed a full-stack web application for database querying and management.

Implemented AWS Textract for modernizing data solutions by extracting unstructured data.

Delivered ECAN Customer 360 for Holcim loading plant data from 6+ source systems into Redshift

Implemented AWS Textract for modernising unstructured-PDF data extraction in pharma DAP

Built incremental data-loading mechanisms supporting hourly, daily and monthly frequencies

Developed full-stack DATALAB web app for cross-region PostgreSQL CRUD with React.js

Project highlights(4)

Eastern Canada Customer 360 – Data Engineer

Overview: This project involves loading plant-related data into a Redshift Data Warehouse for a prominent building material company. Responsibilities: Performed Data Ingestion, ETL Pipeline Development, and View Creation as per requirements. Modernized data solutions by implementing AWS Textract for extracting unstructured data from PDFs.

AWS GlueAWS RedshiftAWS TextractPythonSQLS3

Key outcomes:

  • Developed efficient incremental data pipelines for hourly, daily, and monthly data loads.

  • Built and deployed scheduled and event-triggered ETL pipelines using AWS Glue.

Data Analytics Platform – Data Engineer

Overview: This project for a pharmaceutical company involves onboarding medical datasets through a Data Analytics Platform. Responsibilities: Built Airflow pipelines for ETL processes and platform tasks scheduled as cron jobs. Developed Airflow tasks using shell scripts, Python scripts, and Kubernetes pod operations.

AirflowAWS RedshiftPythonSQLAWS Lambda

Key outcomes:

  • Managed end-to-end data ingestion and ETL pipeline development for critical medical datasets.

  • Ensured data quality through source vs. target DQ checks.

DATALAB Web Application – Data Engineer

Overview: Developed a web application enabling users to perform basic queries on a PostgreSQL database across different EC2 regions. Responsibilities: Implemented user authentication against a PostgreSQL database, enabling users to perform CRUD operations.

ReactPythonPostgreSQLAWS DynamoDBAWS Lambda

Key outcomes:

  • Developed a full-stack web application for secure database querying and schema management.

  • Created a serverless framework application for efficient CRUD operations.

CLI Command Tool

  • Developed a user-interactive custom CLI Command tool using Python's argparse for creating S3 buckets and Glacier vaults.
  • This tool incorporates validation for bucket names, vault names, and regions, and applies specific tags and policies to the created resources.
  • Developed a custom CLI command using Python (argparse) for creating S3 buckets and Glacier vaults.
  • Implemented validation logic for user inputs including bucket name, vault name, and region.
  • Attached specific tags and policies to both S3 buckets and Glacier vaults for resource management.
  • Invoked the CLI command through an Airflow Pipeline using the Airflow REST API for automation.
PythonS3AWS GlacierAirFlow

Key outcomes:

  • Automated AWS S3 bucket and Glacier vault creation with a custom Python CLI tool.

  • Integrated the CLI command into Airflow pipelines, enabling automated resource provisioning.

  • Implemented input validation and resource tagging/policy application for robust automation.

4.3+ years of industry experience

HealthTech1 project
  • •Data Analytics Platform— Data EngineerAirflow · AWS Redshift · Python · SQL +1
InsuranceReported in resume
Logistics & Supply Chain1 project
  • •Eastern Canada Customer 360— Data EngineerAWS Glue · AWS Redshift · AWS Textract · Python +2
Real EstateReported in resume

Ready to work with Nitesh?

Onboard within 48 hours. No long hiring cycles, no recruiter middleman.

At a Glance

LocationIndia
Experience4.3+ years
Work moderemote
Direct hirePossible
Start within48 hours
From$1,581/ month

Single contract. Billed in USD.

Typically responds within 4 business hours.

5-day replacement guarantee
48-hour onboarding, single invoice
Direct chat — no recruiter middleman

Top Skills

Python
10/10
AWS
9/10
SQL
9/10
AWS Glue
9/10
AWS Redshift
9/10
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Owns production deploysGreenfield architectSystem owner
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Ready to onboard in 48 hours

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Nitesh Kumar

Data Engineer