This Associate Data Engineer will manage manufacturing data ingestion into an enterprise data lake using AWS services such as Athena, Redshift, and Kinesis. The role involves configuring ingestion frameworks, performing data validation, and integrating data from SharePoint, OneDrive, SFTP, and LIMS to support analytics platforms.
AWS Data EngineerIng Advanced: Associate Data Engineer
Job requirements
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. Key Responsibilities: 1. Manage manufacturing data ingestion into enterprise data lake and analytics platforms using AWS services. 2. Configure and maintain data ingestion frameworks, mappings, and metadata definitions. 3. Perform data validation, quality checks, and troubleshoot issues in production data pipelines. 4. Integrate data from sources such as SharePoint, OneDrive, SFTP, LIMS, and manufacturing systems. 5. Assist in developing automation solutions for document processing and data extraction with AWS tools. 6. Support analytics platforms by enabling efficient data access and pipeline performance. 7. Create and maintain technical documentation, SOPs, and knowledge-transfer materials. Required Skills: 1. Python 2. SQL 3. Databricks 4. AWS S3 5. AWS Lambda 6. Data engineering and ETL pipeline development 7. Data quality and validation 8. Data integration in cloud environments Preferred Skills: 1. AWS Textract or OCR technologies 2. Experience with Life Sciences or Pharmaceutical domain data 3. Familiarity with LIMS and Manufacturing Execution Systems (MES/EMES) 4. Experience in enterprise data lake environments Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field 2. Completion of relevant AWS or Databricks training courses (certification preferred but not required) Additional Information: Project tenure is 1 year with potential extension.
