The Data Engineer will build and maintain ETL/ELT pipelines, implement automated data quality checks, optimize data storage, and create interactive visualizations. They will manage CI/CD pipelines and deliver production-ready data solutions.
- Years of experience: 8 to 10 years
Focus: Reliability, Automation, and Data Quality. The Engineer turns the architect's blueprint into a working, automated reality.
- Key Responsibilities:
- Build and maintain ETL/ELT pipelines to move data from source to storage.
- Implement automated data quality testing and observability alerts.
- Optimize data storage formats (e.g., Parquet, Delta Lake) for high-speed querying.
- Manage CI/CD pipelines for data code deployment.
- Create interactive visualizations with actionable insights by persona
- Deliverables: Production-ready optimized data pipelines, Cleaned datasets, interactive & intelligent dashboards.
- Tech Stack - AWS
- Data Ingestion & Processing : AWS API Gateway, AWS Lambda, AWS Glue ETL, AWS Glue Crawler
- Data Storage & Analytics : Amazon S3, Amazon Redshift (Data Warehouse), Amazon Athena
- Governance & Security : AWS Lake Formation, AWS IAM, AWS CloudTrail, Amazon CloudWatch
- AI & Analytics : AWS Bedrock
- Visualization : Amazon QuickSight
- Visa Requirement: Preferred USA B1 Business Visa with a minimum validity of 2 years
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Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
