Data Engineer

 Work as part of the data engineering team to build, maintain, and optimize scalable data pipelines for large-scale data processing.
Develop and implement ETL/ELT processes using PySpark, Spark, and other relevant tools to move and transform data from various sources.
Assist in designing and deploying solutions in major cloud platforms such as AWS, Azure, or GCP.
Support the development and maintenance of Big Data processing frameworks and data lakes to handle structured and unstructured data.
Collaborate with data scientists, analysts, and other engineers to ensure data accuracy and availability.
Implement data ingestion strategies, ensuring the secure and efficient movement of data across different storage solutions.
Work on real-time streaming data pipelines and batch data processing to handle high-volume workloads.
Develop and maintain reusable code for data extraction, transformation, and loading (ETL) operations.
Contribute to performance tuning of Spark jobs and data pipelines to ensure scalability and efficiency.
Assist in maintaining governance and data security practices across cloud platforms.