Responsibilities of the Candidate:

Manage manufacturing data ingestion into enterprise data lake and analytics platforms using AWS services.
Configure and maintain data ingestion frameworks, mappings, and metadata definitions.
Perform data validation, quality checks, and troubleshoot issues in production data pipelines.
Integrate data from sources such as SharePoint, OneDrive, SFTP, LIMS, and manufacturing systems.
Assist in developing automation solutions for document processing and data extraction with AWS tools.
Support analytics platforms by enabling efficient data access and pipeline performance.
Create and maintain technical documentation, SOPs, and knowledge-transfer materials.

Requirements:

Python
SQL
Databricks
AWS S3
AWS Lambda
Data engineering and ETL pipeline development
Data quality and validation
Data integration in cloud environments
Preferred Skills:
AWS Textract or OCR technologies
Experience with Life Sciences or Pharmaceutical domain data
Familiarity with LIMS and Manufacturing Execution Systems (MES/EMES)
Experience in enterprise data lake environments
Desired Qualifications:
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field
Completion of relevant AWS or Databricks training courses (certification preferred but not required)
Additional Information:
Project tenure is 1 year with potential extension.Experience Range: Entry-level role with at least 0 to 2 years of hands-on experience in AWS data engineering, ideally including exposure to manufacturing or life sciences data environments.