Data Engineer with Ab Initio

job summary: Randstad Digital is hiring and we're looking for someone like YOU to join our team! If you are seeking a new opportunity, looking to grow in your career, or you know someone who is - we want to hear from you! Take a look at the below opportunity, or feel free to visit RandstadUSA.com to view and apply.

location: Phoenix, Arizona job type: Contract to Perm salary: $56.71 - 69.53 per hour work hours: 8am to 5pm education: Bachelors

responsibilities:

• Pipeline Modernization: Lead the translation and migration of complex enterprise data graphs from Ab Initio (Co>Operating System, EME) into modern GCP-native frameworks using Python, SQL, and Cloud Composer (Apache Airflow).
• BigQuery Architecture: Design and build optimized, highly secure data warehouses and semantic layers within Google BigQuery. Implement strict partitioning, clustering, and slot management strategies to ensure low-latency performance and cost optimization.
• Framework Development: Build reusable, config-driven ingestion and transformation libraries (using Python and Dataflow/Dataproc) to minimize "one-off" pipelines and accelerate enterprise-wide cloud onboarding.
• Data Governance & Risk Mitigation: Enforce data quality rules, automated reconciliation metrics, and robust end-to-end lineage mapping using GCP Dataplex and Data Catalog to adhere to strict enterprise risk and compliance frameworks.
• Automation & GenAI Adoption: Evaluate and utilize modern automation and GenAI-assisted tooling to accelerate schema mapping, legacy code translation (e.g., Ab Initio/SQL to Python/Beam), and test case generation.
• Agile Collaboration: Partner closely with Data Governance, Security, Infrastructure, and downstream Analytics teams in an Agile/Scrum environment to deliver production-ready code via CI/CD pipelines (Git, Cloud Build).

qualifications: 4+ years of Data Engineering experience or equivalent.

3+ years of hands-on experience building, debugging, and maintaining enterprise-scale data pipelines using Ab Initio (and/or parallel architectures like Spark/Informatica) alongside Unix Shell Scripting and Autosys.

2+ years of direct experience deploying production data workloads on Google Cloud Platform, specifically utilizing BigQuery, Cloud Storage (GCS), and Cloud Composer/Airflow.

Advanced expertise in writing and tuning highly complex SQL queries and designing robust data models (Dimensional, Data Vault, or Star Schemas).

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.

,

• Pipeline Modernization: Lead the translation and migration of complex enterprise data graphs from Ab Initio (Co>Operating System, EME) into modern GCP-native frameworks using Python, SQL, and Cloud Composer (Apache Airflow).
• BigQuery Architecture: Design and build optimized, highly secure data warehouses and semantic layers within Google BigQuery. Implement strict partitioning, clustering, and slot management strategies to ensure low-latency performance and cost optimization.
• Framework Development: Build reusable, config-driven ingestion and transformation libraries (using Python and Dataflow/Dataproc) to minimize "one-off" pipelines and accelerate enterprise-wide cloud onboarding.
• Data Governance & Risk Mitigation: Enforce data quality rules, automated reconciliation metrics, and robust end-to-end lineage mapping using GCP Dataplex and Data Catalog to adhere to strict enterprise risk and compliance frameworks.
• Automation & GenAI Adoption: Evaluate and utilize modern automation and GenAI-assisted tooling to accelerate schema mapping, legacy code translation (e.g., Ab Initio/SQL to Python/Beam), and test case generation.
• Agile Collaboration: Partner closely with Data Governance, Security, Infrastructure, and downstream Analytics teams in an Agile/Scrum environment to deliver production-ready code via CI/CD pipelines (Git, Cloud Build).

4+ years of Data Engineering experience or equivalent. 3+ years of hands-on experience building, debugging, and maintaining enterprise-scale data pipelines using Ab Initio (and/or parallel architectures like Spark/Informatica) alongside Unix Shell Scripting and Autosys. 2+ years of direct experience deploying production data workloads on Google Cloud Platform, specifically utilizing BigQuery, Cloud Storage (GCS), and Cloud Composer/Airflow. Advanced expertise in writing and tuning highly complex SQL queries and designing robust data models (Dimensional, Data Vault, or Star Schemas).