AWS Data Engineer

AWS Data Engineer – EXL

Experience: 4–8 Years 
Location: Gurugram 
Work Mode: Hybrid 

About EXL

EXL is a global data and analytics company that combines advanced analytics, technology, and industry expertise to help organizations transform their businesses and make data-driven decisions. This role provides an opportunity to work on enterprise-scale data engineering and cloud transformation initiatives.

Role Overview

EXL is looking for an experienced AWS Data Engineer with strong hands-on expertise in ETL development, SQL, Python, PySpark, Snowflake, and AWS cloud technologies . The ideal candidate will be responsible for designing, developing, and optimizing scalable data pipelines and data processing solutions.

The role requires strong data engineering fundamentals, cloud experience, and the ability to work with large datasets while ensuring data quality, performance, and reliability.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using AWS and modern data engineering technologies.
• Develop efficient and optimized SQL queries for data extraction, transformation, and analysis.
• Build data processing solutions using Python and PySpark .
• Develop and maintain data pipelines integrating multiple structured and semi-structured data sources.
• Work with Snowflake for data warehousing, transformation, and analytical workloads.
• Implement data ingestion and transformation workflows using relevant AWS services .
• Optimize ETL pipelines and data processing jobs for performance, scalability, and cost efficiency.
• Perform data validation, reconciliation, and quality checks across data pipelines.
• Troubleshoot pipeline failures and resolve production data issues.
• Collaborate with data architects, analysts, business stakeholders, and engineering teams to deliver data solutions.
• Follow best practices for coding, testing, documentation, version control, and deployment.
• Contribute to cloud migration and modernization initiatives where required.

Mandatory Skills

• 4–8 years of experience in Data Engineering 
• Strong experience in ETL/ELT Development
• Advanced SQL
• Strong proficiency in Python
• Hands-on experience with PySpark
• Strong experience with AWS
• Hands-on experience with Snowflake
• Good understanding of data warehousing and data pipeline architecture
• Experience working with large-scale datasets

Good-to-Have Skills

• AWS Glue
• Amazon S3
• Amazon Redshift
• AWS EMR
• Apache Airflow
• AWS Lambda
• Data Lake / Lakehouse Architecture
• CI/CD and Git
• Cloud migration and modernization
• Data quality and governance

Candidate Profile

The ideal candidate should have:

• Strong hands-on data engineering experience with AWS, Python, PySpark, SQL, and Snowflake .
• Good understanding of ETL/ELT concepts and data warehouse architecture.
• Strong analytical and problem-solving skills.
• Ability to develop scalable and high-performance data pipelines.
• Good communication and collaboration skills.
• Experience working in Agile development environments is preferred.

Key Skills

AWS | Data Engineering | ETL/ELT | Python | PySpark | SQL | Snowflake | Data Warehousing | Data Pipelines | Cloud Data Engineering 

Location: Gurugram 
Experience: 4–8 Years