Description :

- Design and implement scalable data pipelines using AWS services such as S3, Glue, PySpark, and EMR.

- Develop and maintain robust data transformation scripts using Python and SQL.

- Optimize data storage and retrieval using AWS database services like Redshift, RDS, and DynamoDB.

- Build and manage data warehousing layers tailored to specific business use cases.

- Apply strong ETL and data modeling skills to ensure efficient data flow and structure.

- Ensure high data quality, availability, and consistency to support analytics and reporting needs.

- Work closely with data analysts and business stakeholders to understand data requirements and deliver actionable insights.

Required Qualifications :

- Bachelors or masters degree in computer science, Information Technology, or a related field.

- Hands-on experience with AWS data services such as S3, Glue Studio, Redshift, Athena, and EMR.

- Strong proficiency in SQL and Python for data processing.

- Experience with batch job scheduling and managing data dependencies

Preferred Skills :

- Expertise in data warehousing, ETL frameworks, and big data processing.

- Familiarity with the pharmaceutical domain is a plus.

- Experience with data lake architecture and schema evolution