The role involves designing, developing, and maintaining large-scale data pipelines using AWS services, as well as developing scalable and efficient data models using PySpark and Spark SQL to process massive datasets.

Key Responsibilities :

- Design, develop, and maintain large-scale data pipelines using AWS services such as AWS Glue, Lambda, EMR, and Redshift.

- Develop scalable and efficient data models using PySpark and Spark SQL to process massive datasets.

- Orchestrate containerized applications using Amazon ECS and EC2 to ensure seamless deployment and scalability of data-intensive services across the enterprise.

- Collaborate with stakeholders to translate business requirements into technical specifications, ensuring that data solutions align with long-term strategic objectives.

Required Skills :

- AWS

- Data Engineering

- Python or PySpark

Preferred Skills :

- Experience with big data technologies like Hadoop/Hive/Pyspark/SparkSQL

- Strong understanding of AWS ecosystem including AWS Glue, Lambda, EMR, Redshift, EC2, ECS, S3 etc.

- Proven track record of working effectively in a collaborative, agile environment, with the flexibility to adapt.