Data Engineer

Experience:

• Minimum 4–6 years of experience
• Strong experience in data cleaning and transformation using tools such as SQL, Python (Pandas), or R to ensure data accuracy and consistency.
• Hands-on experience in building and maintaining ETL/ELT pipelines using technologies like SSIS, AWS DMS, AWS Glue, Python, AWS Lambda, ECS, EventBridge, or Spring.
• Good knowledge of database design and experience working with databases such as PostgreSQL, MySQL, MongoDB, Cassandra, SQLite, Athena, and AWS S3.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience developing production-grade data pipelines and data integration solutions in big data environments.
• Understanding of system design, data structures, and algorithms.
• Familiar with data architecture concepts including Data Lakes, Data Warehouses, Data Marts, and Data Virtualization for efficient data storage and access.