Senior Data Engineer (AWS, Big Data, ETL, Netezza, Spark, Kafka, Data Warehousing)

Senior Data Engineer | AWS Cloud | Big Data | ETL | Netezza | Spark | Kafka | Data Platform Modernization Job Summary The ideal candidate will have strong expertise in designing, developing, and supporting scalable data pipelines and distributed systems, along with hands-on experience in Big Data ecosystem tools, AWS services, and real-time data processing.

This role involves working on data platform modernization, cloud migrations, Data Warehousing, and ETL in a fast-paced enterprise environment. Required Technical Skills Cloud Technologies

• Strong experience in AWS Cloud services:
• EMR
• EC2
• S3
• VPC
• RDS
• Redshift
• AWS Glue
• IAM
• Cloud. Watch
• Cloud. Formation
• Experience with:
• Airflow (or AWS Managed Workflows) Databases
• Experience working with:
• Netezza (Mandatory)
• SQL-based systems:
• SQL Server
• PostgreSQL
• Data warehouses:
• Teradata
• Redshift
• Netezza ETL Tools
• Hands-on experience with:
• SSIS
• Pentaho or similar ETL tools Programming & Scripting
• Strong proficiency in:
• SQL
• Shell scripting
• Good to have:
• Python Operating Systems
• Strong experience in Unix/Linux environments. Key Qualifications
• 10+ years of experience in Data Engineering / Big Data / Platform Engineering.

Key Responsibilities

• Design, develop, maintain, and support scalable data pipelines using Big Data and AWS technologies.
• Lead and support data platform migration initiatives (On-Prem to AWS Cloud), ideally with Netezza background.
• Develop and manage ETL/ELT processes using tools like SSIS, Pentaho, or similar.
• Implement and manage AWS services such as:
• EMR
• S3
• EC2
• Redshift
• Glue
• Airflow
• Build and optimize data workflows and orchestration pipelines using Airflow.
• Work with real-time streaming technologies such as:
• Kafka
• Spark Streaming
• Perform data ingestion, transformation, and validation from multiple data sources.
• Optimize SQL queries for performance and scalability.
• Monitor system performance, troubleshoot issues, and ensure system reliability.
• Collaborate with cross-functional teams including:
• Developers
• Architects
• Infrastructure teams.