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.
Key Competencies
- AWS Data Engineering
- ETL/ELT Development
- SQL & Python
- Amazon Redshift
- AWS Lambda
- Amazon S3
- Data Warehousing
- Unit Testing
- Technical Documentation
- Problem Solving
- Team Collaboration
- Multitasking
- Agile Development
Educational Qualification
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant AWS certifications will be an added advantage.
Skills Required
- 3-5 years hands-on experience in Data Engineering.
- Design and develop ETL/ELT pipelines for data ingestion and transformation.
- Proficiency in SQL.
- Proficiency in Python programming.
- Hands-on experience with Amazon Redshift.
- Hands-on experience with AWS Lambda.
- Hands-on experience with Amazon S3.
- Experience with AWS Glue.
- Experience with AWS IAM.
- Experience with Amazon CloudWatch.
- Experience with workflow orchestration tools such as Apache Airflow.
- 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.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Experience with CI/CD pipelines and DevOps practices.
- Knowledge of Spark, PySpark, or Databricks.
- Exposure to AI/ML data pipelines and feature engineering.
- Familiarity with Agile/Scrum development methodologies.
- AWS Certification (Developer Associate or Data Engineer Associate).
What We Do
Choosing a digital partner is about more than capabilities — it’s about collaboration and character. Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments. At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations. Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale. Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact. We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition. At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward. For more information, visit www.exlservice.com.
