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.