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# Lead Data Engineer Data Migration

- **Company:** UnivEdge Consulting LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Application Frameworks, Microsoft Azure, Code Review, Databases, Continuous Integration, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Migration, Data Warehousing, IBM DB2, IBM InfoSphere DataStage, IBM WebSphere MQ, Python (Programming Language), Enterprise Messaging Systems, Oracle (Applications), Performance Tuning, SQL Databases, Workflow Management Systems, Data Ingestion, Snowflake, Apache Spark, Git, Microsoft Fabric, Pyspark, Deployment Automation, Apache Kafka, Data Pipelines
- **Published:** October 15, 2026
- **Apply:** https://www.dice.com/job-detail/f4037e35-2910-4fdc-866a-9e29e444b009

## About the Role

With preference for those who have hands-on experience with DataStage, Microsoft Fabric, or similar data modernization/migration programs.

Skills: Microsoft Fabric, DataStage, Azure, SQL, Python, PySpark/Apache Spark, Data Factory, ETL, Data Warehousing, Data Engineering, CI/CD, * 4-6 years of experience in data engineering, ETL development, data migration, or data warehousing.

 * Strong hands-on experience with SQL, Python/PySpark, ETL, and data pipeline development.
 * Experience with Microsoft Fabric/Azure, including Data Factory, OneLake, Lakehouse/Warehouse, or Synapse.
 * Experience working with enterprise source systems such as DB2, IBM MQ, Snowflake, Oracle, or Kafka.
 * Strong understanding of data modelling, data integration, performance optimization, and CI/CD.

Good to Have:

 * Prior experience with IBM DataStage, including DataStage jobs, transformations, and migration/modernization programs.
 * Experience in DataStage-to-Fabric or similar ETL modernization projects.
 * Exposure to Azure DevOps, Git, and automated deployment frameworks.

## Description

* Lead the design, development, and deployment of scalable data pipelines and ETL workflows for DataStage to Microsoft Fabric migration.
 * Develop and optimize pipelines using Microsoft Fabric Data Factory, OneLake, Lakehouse/Warehouse, and Apache Spark/PySpark.
 * Design and implement data ingestion, transformation, integration, and migration solutions across structured and unstructured data sources.
 * Perform source-to-target mapping and translate existing DataStage ETL logic into scalable Fabric-based solutions.
 * Work with enterprise source systems including IBM DB2, IBM MQ, Snowflake, Oracle, Kafka, and other databases/messaging platforms.
 * Develop complex data transformations and processing using SQL and Python/PySpark.
 * Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
 * Implement data quality, governance, security, and monitoring best practices across the data platform.
 * Lead code reviews, technical design discussions, troubleshooting, and resolution of complex data engineering issues.
 * Collaborate with QA, Data Architects, BI Engineers, and business teams to deliver migration solutions aligned with functional and technical requirements.
 * Support CI/CD and deployment automation using Azure DevOps and relevant orchestration tools.
 * Mentor junior/mid-level data engineers and contribute to engineering standards, reusable frameworks, and technical documentation.