Associate Data Engineer
Bangalore, Karnataka, India
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingManage manufacturing data ingestion into enterprise data lake and analytics platforms
Integrate data from SharePoint, OneDrive, SFTP, LIMS and manufacturing systems
Perform data validation, quality checks, and troubleshoot production pipelines
Configure and maintain data ingestion frameworks, mappings, and metadata definitions
Assist in building document processing and data extraction automation on AWS
From the employer’s posting
Manage manufacturing data ingestion into enterprise data lake and analytics platforms using AWS services.
Integrate data from sources such as SharePoint, OneDrive, SFTP, LIMS, and manufacturing systems.
Perform data validation, quality checks, and troubleshoot issues in production data pipelines.
Configure and maintain data ingestion frameworks, mappings, and metadata definitions.
Assist in developing automation solutions for document processing and data extraction with AWS tools.
Tools in this posting
- Python
- SQL
- AWS
- Databricks
- Redshift
- S3
Source — Tool mentions in context
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. Employment type
Specialization - AWS Data EngineerIng Advanced: Associate Data Engineer Job requirements
Primary Skills - Athena, SNS, SQS, CloudWatch, Kinesis, Redshift Specialization
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · 1 day ago
- Recorded sightings
- 3
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
Primary Skills
- Athena, SNS, SQS, CloudWatch, Kinesis, Redshift
Specialization
- 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.
Employment type
Employee
Source details
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- Pay
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- Location & working pattern
Bangalore, Karnataka, India
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