Returnship - AWS Data Engineer
Chennai, Tamil Nadu, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid remote
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingBuild and manage ETL/ELT workflows for structured and unstructured data
Design and maintain Data Lakes on AWS
Ingest data from APIs, databases, files, and streaming platforms
Monitor, troubleshoot, and optimize data workflows and Spark applications
From the employer’s posting
Build and manage ETL/ELT workflows for processing structured and unstructured data.
Design and maintain Data Lakes on AWS.
Perform data ingestion from multiple sources including APIs, databases, files, and streaming platforms.
Monitor, troubleshoot, and optimize data workflows for performance and reliability.
What you’ll bring
All qualificationsCore experience
- Strong expertise in Python
- Hands-on experience with PySpark
- Proficiency in SQL and query optimization
Qualification wording
Strong expertise in Python
Hands-on experience with PySpark
Proficiency in SQL and query optimization
Tools in this posting
- Python
- SQL
- AWS
- Spark
- PySpark
Source — Tool mentions in context
Key Responsibilities - Design, develop, and maintain scalable data pipelines using Python and PySpark. - Build and manage ETL/ELT workflows for processing structured and unstructured data.
Mandatory Skills - Strong expertise in Python - Hands-on experience with PySpark
- Hands-on experience with PySpark - Proficiency in SQL and query optimization
- Develop and optimize Spark applications to handle large-scale datasets efficiently. - Implement cloud-native data solutions using AWS services. - Design and maintain Data Lakes on AWS.
- Implement cloud-native data solutions using AWS services. - Design and maintain Data Lakes on AWS. - Perform data ingestion from multiple sources including APIs, databases, files, and streaming platforms.
- Build and manage ETL/ELT workflows for processing structured and unstructured data. - Develop and optimize Spark applications to handle large-scale datasets efficiently. - Implement cloud-native data solutions using AWS services.
- Strong expertise in Python - Hands-on experience with PySpark - Proficiency in SQL and query optimization
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 18, 2026 · 41 days ago
- Recorded sightings
- 113
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python and PySpark.
- Build and manage ETL/ELT workflows for processing structured and unstructured data.
- Develop and optimize Spark applications to handle large-scale datasets efficiently.
- Implement cloud-native data solutions using AWS services.
- Design and maintain Data Lakes on AWS.
- Perform data ingestion from multiple sources including APIs, databases, files, and streaming platforms.
- Monitor, troubleshoot, and optimize data workflows for performance and reliability.
- Ensure data quality, integrity, security, and governance standards are followed.
- Implement automation and orchestration of data workflows using scheduling tools.
- Collaborate with cross-functional teams for requirement gathering and solution design.
- Conduct code reviews, unit testing, and performance tuning.
- Prepare technical documentation and deployment procedures.
- Support production incidents and perform root cause analysis.
Mandatory Skills
- Strong expertise in Python
- Hands-on experience with PySpark
- Proficiency in SQL and query optimization
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chennai, Tamil Nadu, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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