AWS Data Engineer
EXL · India
Business Consulting and Services · 10,001+ employees
5 h ago
Mid (2-5 yrs)
Full-time
India
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About the role
Design, develop, and optimize scalable ETL/ELT pipelines while maintaining robust data infrastructure using AWS cloud services. Collaborate with cross-functional teams including BI, AI/ML, and Infrastructure to deliver reliable data platform solutions.
What they look for
AWS
Data Engineering
ETL/ELT Pipelines
SQL
Python
Amazon Redshift
AWS Lambda
Amazon S3
AWS Glue
AWS IAM
Amazon CloudWatch
Apache Airflow
Data Warehousing
Dimensional Data Modeling
Git
Unit Testing
Requirements
Requires 3–5 years of hands-on experience in data engineering with proficiency in SQL, Python, and AWS services. A bachelor's degree in Computer Science, Information Technology, Engineering, or a related field is required.
Full description
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines for data ingestion and transformation.
- Build and maintain robust data pipelines using AWS cloud services.
- Partner with Business Intelligence (BI), AI/ML, and Infrastructure teams to deliver reliable and scalable data platform solutions.
- Develop efficient SQL queries and Python scripts for data processing, automation, and analytics.
- Create and maintain technical documentation, including solution designs, data flow diagrams, and operational guides.
- Develop comprehensive unit tests and perform code reviews to ensure high-quality, reliable, and maintainable code.
- Monitor, troubleshoot, and optimize data pipelines to ensure performance, scalability, and reliability.
- Work on multiple projects simultaneously while managing priorities in a fast-paced environment.
- Follow coding standards, best practices, and data governance guidelines.
Required Skills & Qualifications
- 3–5 years of hands-on experience in Data Engineering.
- Strong experience in designing and developing ETL/ELT pipelines.
- Proficiency in SQL and Python programming.
- Hands-on experience with AWS services, including:
- Amazon Redshift
- AWS Lambda
- Amazon S3
- AWS Glue (preferred)
- AWS IAM
- Amazon CloudWatch
- Experience with workflow orchestration tools such as Apache Airflow (preferred).
- Understanding of data warehousing concepts and dimensional data modeling.
- Knowledge of version control systems such as Git.
- Experience writing unit tests and following software development best practices.
- Strong analytical, problem-solving, and debugging skills.
- Excellent communication and documentation skills.
- Ability to manage multiple tasks and work effectively in a collaborative environment.
Preferred Skills
- Experience with CI/CD pipelines and DevOps practices.
- Knowledge of Spark, PySpark, or Databricks is an advantage.
- Exposure to AI/ML data pipelines and feature engineering.
- Familiarity with Agile/Scrum development methodologies.
- AWS Certification (Developer Associate or Data Engineer Associate) is a plus.
