Data Engineer with AWS

Virtusa; Hyderabad, Chennai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Virtusa is looking for a senior data engineering professional to lead design and optimization of scalable data pipelines in AWS. The role emphasizes Redshift modeling, data lake architectures on S3, and real-time processing with PySpark.

The candidate will collaborate with cross-functional teams, enforce data governance and security practices, and drive CI/CD powered deployment and automation across data platforms.

Qualifications

• 10+ years in Data Engineering and Data Warehousing.
• Hands-on AWS Glue, Redshift, S3, EMR, and Athena.
• Design scalable batch and real-time data pipelines with PySpark and Python.
• Redshift modeling, S3 data lake architecture.
• Workflow orchestration with Airflow or Step Functions.
• CI/CD integration, deployment automation, and infra support.
• Data quality, encryption, IAM roles, governance policies.
• Advanced SQL optimization for large-scale data; cross-functional collaboration.

Responsibilities

• Collaborate with architects, engineers and stakeholders to deliver data solutions.
• Design and optimize data pipelines for performance, reliability and cost.
• Contribute to data governance, security policies, and data quality checks.

Skills

Data Engineering

Data Warehousing

SQL

Collaboration

DevOps

Tools

AWS Glue

Amazon Redshift

Amazon S3

EMR

Athena

PySpark

Python

Apache Airflow

AWS Step Functions

CI/CD

IAM

Encryption

Job description

Job Description

• Experience Required: 10+ years in Data Engineering and Data Warehousing.
• Core AWS Services: Hands-on expertise with AWS Glue, Amazon Redshift, Amazon S3, EMR, and Athena.
• Pipeline Development: Design, build, and optimize scalable batch and real-time data pipelines using PySpark and Python.
• Data Warehousing: Expertise in Amazon Redshift modeling, optimization, and S3 data lake architecture.
• Workflow Orchestration: Manage dependencies and automate tasks using Apache Airflow or AWS Step Functions.
• Infrastructure & DevOps: CI/CD integration, infrastructure support, and deployment automation.
• Data Quality & Security: Implement data validation, encryption, IAM roles, and governance policies.
• Query Performance: Advanced SQL optimization for large-scale enterprise data.
• Collaboration: Partner with cross-functional teams, architects, and stakeholders to deliver solutions.