Key Responsibilities Design, develop, and maintain robust ETL/ELT pipelines to ingest, process, and transform data from multiple sources. Build and optimize scalable data warehouses, data lakes, and data marts. Develop and maintain batch and real-time data processing solutions. Collaborate with Data Analysts, Data Scientists, and Business stakeholders to understand data requirements. Ensure data quality, integrity, security, and governance across the organization. Monitor and troubleshoot data pipelines and production data systems. Optimize database performance, query execution, and storage utilization. Implement data validation, monitoring, and alerting mechanisms. Document data architecture, workflows, and technical specifications. Stay updated with emerging data engineering technologies and best practices. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. 3+ years of experience in Data Engineering or related roles. Strong proficiency in SQL and database concepts. Experience with Python, Scala, or Java. Hands-on experience with ETL/ELT tools and frameworks. Knowledge of data warehousing concepts and dimensional modeling. Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. Experience with big data technologies such as Apache Spark, Apache Kafka, and Apache Hadoop. Familiarity with CI/CD practices and version control systems.