About the role

AWS Data Engineer

Experience:	6 – 8 Years
Location:	Hyderabad, Chennai, Bengaluru, Noida, Gurugram, Pune
Work Mode:	Hybrid
Position:	AWS Data Engineer

Role Overview

We are looking for an experienced AWS Data Engineer with 6 – 8 years of hands-on experience in designing, developing, and maintaining scalable data engineering solutions on AWS. The candidate should have strong expertise in Python, PySpark, SQL, AWS data services, ETL development, and cloud-based data pipelines.

Key Responsibilities

Design, develop, and maintain scalable and reliable data pipelines on AWS Cloud.
Develop robust ETL/ELT workflows using AWS Glue ETL and Glue Data Catalog.
Build data processing solutions using Python, PySpark, and SQL.
Work with Amazon S3 for data storage, ingestion, and data lake solutions.
Develop and manage serverless data processing using AWS Lambda.
Implement event-driven data workflows using Amazon EventBridge.
Orchestrate complex data pipelines and workflows using AWS Step Functions.
Use Amazon Athena for querying and analyzing data stored in Amazon S3.
Develop efficient, reusable, and optimized data transformation processes.
Monitor, troubleshoot, and optimize data pipelines for performance, scalability, and reliability.
Collaborate with data architects, analysts, application teams, and business stakeholders to understand data requirements.
Ensure data quality, security, governance, and adherence to AWS best practices.
Participate in code reviews, technical discussions, and continuous improvement initiatives.

Required Skills

6 – 8 years of experience in Data Engineering.
Strong programming skills in Python.
Strong hands-on experience with PySpark.
Excellent knowledge of SQL and data manipulation.
Strong experience with AWS Cloud and AWS data services.
Hands-on experience with:

Amazon S3
AWS Glue ETL
AWS Glue Data Catalog
AWS Lambda
Amazon EventBridge
AWS Step Functions
Amazon Athena

Experience in building and maintaining ETL/ELT data pipelines.
Good understanding of data lakes, cloud data architecture, and distributed data processing.
Strong troubleshooting and problem-solving skills.

Preferred Qualifications

Experience working with large-scale datasets and distributed processing frameworks.
Knowledge of AWS security, IAM, monitoring, and cost optimization.
Understanding of data warehousing and modern cloud data engineering practices.
Experience working in Agile/Scrum environments.
Strong communication and stakeholder management skills.