Technical Role :
- Design, build, and maintain scalable data pipelines to ingest, process, transform, and deliver large volumes of structured and unstructured data.
- Develop and optimize ETL/ELT frameworks to support data integration, reporting, analytics, and business intelligence initiatives.
- Build and maintain Data Lake, Data Warehouse, and Data Mart solutions to support enterprise data consumption.
- Implement automated data quality checks, validation controls, monitoring, and reporting to ensure data accuracy, consistency, and reliability.
- Design and manage batch processing workflows for large-scale data processing and transformation.
- Collaborate with business stakeholders, analytics teams, and technology partners to understand data requirements and deliver scalable solutions.
- Optimize data pipelines and storage architectures for performance, scalability, and cost efficiency.
- Ensure compliance with data governance, security, and regulatory standards.
- Support data modeling activities including fact and dimension design, data cataloging, and metadata management.
- Troubleshoot production data issues and perform root cause analysis to maintain platform reliability.
Tech stack to look for in profile :
1. Python/PySpark
2. SQL
3. Data lake, Data Warehouse, Data Mart
4. AWS : EMR, Glue, S3, Data Catalog, Redshift
5. Airflow
6. Batch processing
Pay: Up to ₹4,000,000.00 per year
Work Location: In person
