IT & Software

SAS Engineer

Atos

Manchester · England · United Kingdom

Overview

In this role you will support migrating SAS workloads and related data processes to modern cloud-based platforms. You will collaborate with SMEs, architects, and delivery teams to design, build, and optimize SAS migration solutions while maintaining data quality and integrity. You will address data flows, validation, and migration scripting to enable successful cloud transformations. This position sits in Atos Data Analytics & AI Practice, offering opportunities to shape scalable data solutions in a security-conscious, cross-functional environment. You will contribute to a growing data community while delivering tangible business outcomes.

Pay / Benefits

  • 25 days paid leave + National Holidays
  • Pension Scheme – contributions matched up to 10%
  • Private Medical Cover
  • Income Protection
  • Life Assurance
  • Flex Benefits Program

Responsibilities
  • Build, configure, and implement SAS components and workloads on target cloud platforms.
  • Develop and optimise SAS data flows, ETL processes, and migration scripts for cloud migration.
  • Execute data migration, validation, reconciliation, and cleansing to ensure accuracy and integrity.
  • Support testing, defect resolution, troubleshooting, and technical documentation throughout the migration lifecycle.
  • Collaborate with SMEs, architects, and delivery teams to meet milestones and project objectives.

Key requirements
  • Strong experience in SAS engineering, development, and administration.
  • Proven ETL development, data integration, and data pipeline implementation.
  • Experience with data migration, validation, reconciliation, and data quality processes.
  • Scripting experience and ability to automate migration and transformation activities.
  • Experience with cloud-based data platforms and modern data architectures.
  • collaboration
  • communication
  • problem-solving
  • SAS engineering, development, and administration
  • ETL development, data integration, data pipeline implementation
  • data migration, validation, reconciliation, data quality

Reference: WJ-799_20871848

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