Experience Requirements:

• 4+ years of programming languages such as Python (preferably)

• Experience with big data technologies (e.g., Spark, Kafka), cloud platforms (e.g., AWS, Azure), and containerized environments (Docker, Kubernetes)

• Solid understanding of data warehousing, ETL processes, and data pipeline design

Responsibilities:

• Design, implement, and optimize scalable data pipelines and architectures for large-scale data processing

• Ensure data quality, integrity, and availability by establishing best practices and monitoring systems

• Troubleshoot and resolve data-related issues to ensure continuous improvement

• Drive innovation by evaluating new data technologies and tools to improve data engineering practices