Data Engineer

Virtue Tech Inc.

Responsibilities Legacy Data Extraction: Design, build, and optimise high-throughput data extraction pipelines from legacy IBM DB2 transactional databases without locking production environments. Cloud Platform Build: Develop production-grade ETL pipelines and data lake storage architectures directly on the target AWS data platform. Schema and Code Modernisation: Collaborate with the Solution Architect and Tech Lead to migrate complex legacy schemas, handle large object (LOB) data types, and convert legacy stored procedures into cloud-native equivalents. Performance Tuning: Troubleshoot and resolve pipeline bottlenecks, optimise PySpark/Glue jobs, and handle massive data volumes under a strict Time and Materials delivery model. Requirements Enterprise Relational Databases: 4+ years of deep, hands-on experience with IBM DB2 (understanding of DB2 utilities, transaction logs, locking behaviour, and Change Data Capture/CDC mechanisms). Core AWS Data Stack: Advanced proficiency with AWS Glue, AWS DMS (Database Migration Service), AWS SCT (Schema Conversion Tool), and Amazon S3 data lake patterns. Big Data Frameworks: Heavy experience writing optimised PySpark, Spark SQL, or Scala jobs within AWS Glue or EMR. Data Warehousing: Direct exposure to target cloud data warehouses like Amazon Redshift, AWS Athena, or modern open table formats (Delta Lake, Apache Iceberg). Infrastructure as Code (IaC): Basic familiarity with Terraform or AWS CloudFormation to deploy data pipelines safely. #J-18808-Ljbffr

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