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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
• CloudWatch
• CloudFormation

• 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.

See also

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