Cloud Analytics Migration Engineer (SAS to GCP)

Kelly Services; Dearborn (MI); Hybrid; USD 125,000 - 140,000; Full time

Benefits offered by this job

Bonus eligible

Medical, Dental, and Vision Insurance

Vacation Time

Stock Options

Job summary

Kelly Services is seeking an Analytics Migration Engineer to lead the migration of analytical code, data pipelines, and models from on-prem to Google Cloud Platform, ensuring continuity of outputs and validated AI/ML models across environments.

The role is hybrid, three days a week in Dearborn, MI, and involves collaborating with data engineering, analytics, and data science teams to build a scalable cloud analytics ecosystem and ensure accuracy across reporting and modeling.

Qualifications

• Bachelor's degree in a quantitative or technical field.
• Experience with SAS 9.4, SAS Viya, Python and SQL.
• Experience with cloud data platforms or on-prem-to-cloud migrations.
• Experience with BigQuery and data validation across environments.
• Ability to work across data engineering, analytics, and business stakeholders.

Responsibilities

• Migrate legacy analytical code and data pipelines to GCP with refactoring for cloud architecture.
• Validate outputs and reconcile results between on-prem and cloud environments.
• Perform regression testing and QA across datasets, dashboards, and models.
• Support migration of AI/ML models and optimize analytics workflows in the cloud.
• Collaborate with cross-functional teams to maintain business-critical reporting during migration.

Skills

SAS 9.4

SAS Viya

Python

SQL

Cross-functional collaboration

Data validation

Root cause analysis

Education

Bachelor's Degree in a quantitative or technical field

Tools

BigQuery

Airflow

Cloud Composer

Vertex AI

GCP / AWS / Azure cloud platforms

Job description

Kelly Services is seeking an Analytics Migration Engineer to lead the migration of analytical code, data pipelines, and models from on-prem to Google Cloud Platform, ensuring continuity of outputs and validated AI/ML models across environments.

The role is hybrid, three days a week in Dearborn, MI, and involves collaborating with data engineering, analytics, and data science teams to build a scalable cloud analytics ecosystem and ensure accuracy across reporting and modeling.