Summary
✨ AI‑Generated
A data engineering role focused on scalable pipelines, distributed systems, cloud migration, real-time processing, data warehousing, and ETL. The position requires strong AWS, SQL, Unix/Linux, and scripting expertise, with Python considered beneficial.
Highlights
Work on scalable data platforms, distributed systems, cloud migration, real-time processing, data warehousing, and ETL in an enterprise environment. The role provides broad exposure to AWS services and modern data platform technologies.
Description
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 Airflow (or AWS Managed Workflows) Databases
• Experience working with: Netezza is mandatory SQL-based systems: SQL Server and Postgres SQL Data warehouses: Teradata, Redshift, Netezza ETL Tools
• Hands-on experience with:SSIS Programming & Scripting Strong proficiency in: SQL Shell scripting
• Good to have: Python Operating Systems
• Strong experience in Unix/Linux environments
• Key Qualifications10+ 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, and Airflow Build and optimize data workflows and orchestration pipelines using Airflow Work with real-time streaming technologies such as Kafka and Spark Streaming
• Perform data ingestion, transformation, and validation from multiple data sourcesOptimize SQL queries for performance and scalability
• Monitor system performance, troubleshoot issues, and ensure system reliability
• Collaborate with cross-functional teams including developers, architects, and infrastructure teams
“Tekshapers is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.”
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