AWS Data Engineer Job ID: 410674

Viraaj HR Solutions; Delhi; On-site; INR 1,800,000 - 2,800,000; Full time

Benefits offered by this job

Cloud certification sponsorship

Direct exposure to enterprise-scaleAWS

Growth acceleration for high achievers

Job summary

Viraaj HR Solutions is seeking an experienced Data Engineer to design and implement scalable data pipelines on AWS, enabling real-time analytics and ML model training. You will build data lakes on S3, implement governance, and optimize Redshift/Snowflake performance where integrated.

You will collaborate with analytics and ML teams to deliver clean, curated datasets for dashboards and model training, in a fast-paced, collaboration-driven environment at our Delhi office.

Qualifications

• Must have hands-on experience designing data pipelines in AWS (Glue, Lambda, S3).
• Experience with data lake/warehouse architectures and governance.
• Strong Python and SQL skills for ETL/ELT development and performance tuning.

Responsibilities

• Design and implement scalable ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions for batch and real-time data ingestion.
• Build and maintain data lakes on S3 with partitioning, Glue Data Catalog, and governance using IAM and Lake Formation.
• Orchestrate data workflows via AWS MWAA or Step Functions, monitor pipeline health, and ensure SLA compliance.

Skills

AWS Glue

Amazon S3

AWS Lambda

Python

SQL

ETL/ELT

Amazon Redshift

Amazon Athena

Tools

AWS Step Functions

AWS MWAA

Apache Airflow

Job description

About the Opportunity

A dynamic talent solutions firm operating at the intersection of cloud infrastructure and data engineering, we partner with enterprises to build scalable, secure, and high-performance data platforms on AWS. Our engineers architect, deploy, and optimize data pipelines, lakes, and warehousing solutions that power real-time analytics, machine learning, and business intelligence across industries.

Role & Responsibilities

• Design and implement scalable ETL/ELT pipelines using AWS Glue, Lambda, and Step Functions for batch and real-time data ingestion.
• Build and maintain data lakes on S3 with proper partitioning, cataloging (Glue Data Catalog), and governance using IAM and Lake Formation.
• Orchestrate data workflows via AWS MWAA or Step Functions, monitor pipeline health, and ensure SLA compliance.
• Optimize Redshift or Snowflake (if integrated) for performance and cost using materialized views, distribution keys, and query tuning.
• Implement data quality checks, lineage tracking, and alerting using CloudWatch, Athena, and custom Python scripts.
• Collaborate with analytics and ML teams to deliver clean, curated datasets for dashboards and model training.

Skills & Qualifications

• Must-Have
• AWS Glue
• Amazon S3
• AWS Lambda
• Amazon Redshift
• Amazon Athena
• Python
• SQL
• ETL/ELT
• Preferred
• AWS Step Functions
• AWS MWAA
• Apache Airflow

Benefits & Culture Highlights

• Onsite collaborative environment with access to cloud certification sponsorships.
• Direct exposure to enterprise-scale AWS data architectures and cross-functional teams.
• Fast-paced, learning-driven culture with growth acceleration for high performers.