Purpose of the Role
To design, build, and optimise data pipelines and integration processes required for migrating SAS estate (including SAS 9.4 and Viya 3.5 components) to SAS Viya 4 on DPS AWS. The Data Engineer will ensure data integrity, performance, and compliance throughout the migration and operational phases.
Key Responsibilities
- Data Pipeline Development:
- Design and implement ETL processes to migrate data from Legacy SAS environments to SAS Viya 4.
- Optimise data flows for performance and scalability in a cloud-native architecture.
- Integration & Transformation:
- Work with SAS developers to refactor existing jobs and ensure compatibility with Viya 4.
- Implement data transformations and validation rules to maintain accuracy and consistency.
- Automation & CI/CD:
- Develop automated workflows for data ingestion and processing using DevOps tools (Jenkins, Git).
- Integrate data pipelines into CI/CD frameworks for continuous delivery.
- Data Quality & Governance:
- Ensure compliance with data governance, security, and GDPR standards.
- Implement monitoring and alerting for data quality and pipeline health.
- Collaboration:
- Work closely with architects, business analysts, and test teams to align data solutions with migration requirements.
- Support UAT and production readiness activities by providing test data and validation scripts.
Required Skills & Experience
Strong experience in:
Building and managing ETL pipelines using tools such as SAS Data Integration, Pentaho, or Talend.
Working with SAS technologies (SAS 9.4, SAS Viya 3.x/4).
Proficiency in:
SQL, Python, and Scripting for data processing.
Cloud platforms (AWS) and containerisation (Docker, Kubernetes).
Familiarity with:
Data modelling, performance tuning, and large-scale data migration.
Agile delivery and DevOps practices.
Desirable Qualifications
- Certifications in SAS, AWS Data Engineering, or equivalent.
- Experience in government or regulated environments.
- Knowledge of data virtualisation tools (eg, Denodo).