AWS Data Engineer

Infosys; Bengaluru; On-site; INR 1,000,000 - 1,800,000; Full time

Job summary

Infosys is seeking an AWS Data Engineer to design and maintain scalable ETL/ELT pipelines on AWS, including Glue, EMR, Redshift, S3, and Lambda. You will build data ingestion workflows, develop data lakes and warehouses, and ensure data quality and security across large datasets.

The role requires 3–5 years of cloud data engineering experience, strong problem-solving, and excellent communication to collaborate with analysts, data scientists, and application teams.

Qualifications

• Bachelor's degree in CS/IT or related field.
• 3–5 years of relevant Data Engineering experience.
• Experience with cloud-based data platforms and analytics environments.
• Strong problem-solving and communication skills.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines on AWS.
• Build and optimize data ingestion and transformation workflows.
• Develop and manage data lakes and data warehouse solutions.
• Work with large-scale structured and unstructured datasets.
• Implement data quality, governance, and security best practices.
• Optimize data processing performance and cost efficiency.
• Collaborate with business analysts, data scientists, and application teams.
• Monitor, troubleshoot, and resolve data pipeline issues.
• Support data migration and modernization initiatives.
• Create technical documentation and maintain data architectures.

Skills

AWS Glue

AWS EMR

Amazon Redshift

S3

SQL

Python

PySpark

Spark

ETL

Data Warehousing

Data Lake

Data Pipeline

Kinesis

Airflow

Databricks

Education

Bachelor's degree in Computer Science or IT

Tools

Terraform

CI/CD Pipelines

Kafka

Snowflake

Databricks

Job description

AWS Data Engineer Technology-AWS Glue, EMR, Redshift, Athena, S3, Lambda, Python, SQL, PySpark, Spark, ETL, Data Pipeline, Data Lake, Data Warehouse, Kinesis, Airflow, Databricks, AWS Data Engineer.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines on AWS.
• Build and optimize data ingestion and transformation workflows.
• Develop and manage data lakes and data warehouse solutions.
• Work with large-scale structured and unstructured datasets.
• Implement data quality, governance, and security best practices.
• Optimize data processing performance and cost efficiency.
• Collaborate with business analysts, data scientists, and application teams.
• Monitor, troubleshoot, and resolve data pipeline issues.
• Support data migration and modernization initiatives.
• Create technical documentation and maintain data architectures.

Required Skills

AWS Glue AWS EMR Amazon Redshift Amazon S3 AWS Athena AWS Lambda SQL Python PySpark / Apache Spark ETL Development Data Warehousing Data Lake Architecture

Good-to-Have Skills

AWS Kinesis Apache Airflow Kafka Snowflake Databricks Terraform CI/CD Pipelines Hadoop Ecosystem

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or related field.
• 3-5 years of relevant Data Engineering experience.
• Experience working in cloud-based data platforms and analytics environments.
• Strong problem-solving and communication skills.