Data Engineer – SSIS Migration Project
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Summary
Remote data engineer role focused on migrating ETL workloads from SSIS 2016 to SQL Server 2022: upgrading and validating packages, updating connection managers/parameters, executing via SSISDB and CA Workload, and documenting results in Azure DevOps. Core stack: SQL Server, T-SQL, Visual Studio, SSMS, Azure DevOps.
This is a remote position.
Job Objective: Data Engineer with solid experience in SQL Server Integration Services (SSIS) to support the migration of ETL workloads from SSIS 2016 to SSIS 2022.The role focuses on upgrading packages, validating compatibility, and ensuring data consistency across environments using structured sprint-based delivery.
Responsibilities:
- Upgrade and validate SSIS projects to SQL Server 2022.
- Update connection managers, parameters, and environment variables to align with new configuration models.
- Execute and validate workloads through SSISDB and CA Workload (ESP dSeries) or similar orchestration tools.
- Compare execution results between versions to ensure data and functional parity.
- Document results, issues, and configurations in Azure DevOps.
- Collaborate with Technical Leads, QA, and DevOps teams during validation and release cycles.
Requirements
Bachelor’s degree in computer science, Software Engineering, or related field.
Preferred certifications: Microsoft Certified Data Engineer, SSIS, Azure DevOps.
3–5 years in data engineering roles, with hands-on SSIS migration, ETL validation, and use of Visual Studio, SSMS, and Azure DevOps.
Required Skills:
- Proven experience with SSIS development, configuration, and migration.
- Strong SQL Server and T-SQL skills for ETL troubleshooting and optimization.
- Experience using Visual Studio 2022, SQL Server Management Studio (SSMS), and Azure DevOps.
- Familiarity with CA Workload (ESP dSeries) or equivalent job automation/orchestration tools.
- Understanding of environment variable management, package parameters, and catalog deployment (SSISDB).
- Experience validating data pipelines and documenting results for QA/UAT.
- Strong problem-solving, communication, and documentation skills.
Soft Skills:
- Analytical thinking: assess compatibility and validate data integrity.
- Problem-solving: troubleshoot migration and execution issues.
- Communication: document findings and collaboration across teams.
- Time management: delivery within sprint cycles and tight timelines.
- Team collaboration: work effectively with QA, DevOps, and technical leads.
Benefits
We offer a competitive package with several advantages.