$125000 - $140000
Our client is seeking an Analytics Migration Engineer to join their team on a full-time basis. In this role, you will lead the migration and modernization of analytical code, data pipelines, and statistical models from legacy on-premise environments to Bitquery in modern cloud platforms (GCP), ensuring analytical continuity as outputs, data, and AI/ML models are validated across environments. This role is hybrid 3 days a week in Dearborn, MI
You will work across data engineering, analytics, and data science teams to maintain business-critical reporting and modeling while enabling a scalable, cloud-based analytics ecosystem. This role blends migration execution, validation, and optimization, giving you the chance to help shape a modern, future-ready analytics environment.
Required Skills & Experience
Bachelor's Degree in a quantitative or technical field (Computer Science, Data Science, Statistics, Mathematics, Engineering, or related)
Experience with analytical programming languages such as SAS 9.4, SAS Viya, Python, and SQL
Experience with cloud data platforms (GCP, AWS, or Azure) or supporting on-prem to cloud migrations
Experience with Bigquery
Experience validating data outputs, dashboards, and statistical or machine learning models
Strong understanding of data structures, ETL processes, and analytical workflows
Experience troubleshooting data discrepancies and performing root cause analysis
Ability to work across cross-functional teams, including data engineering, analytics, and business stakeholders
Strong attention to detail and commitment to data accuracy and quality
Desired Skills & Experience
Experience migrating SAS-based analytical environments to cloud platforms
Experience validating and deploying machine learning models in cloud environments (e.g., Vertex AI)
Familiarity with automated testing frameworks and data pipeline orchestration tools (e.g., Airflow, Cloud Composer)
Experience optimizing analytical code and queries for performance and scalability in the cloud
Experience supporting large-scale analytics or CRM data ecosystems
Strong documentation and process design skills to support repeatable migration frameworks
Ability to translate technical findings into clear insights for non-technical stakeholders
Experience in large enterprise or highly regulated data environments
What You Will Be Doing
Migrate legacy analytical code (SAS, SQL, Python) and data pipelines from on-prem environments to GCP, refactoring workflows for modern cloud architecture and best practices
Validate and reconcile outputs between legacy and cloud environments to ensure consistency and accuracy across data, reporting, and models
Perform regression testing and quality assurance across datasets, dashboards, and statistical/ML models to confirm functional parity post-migration
Support migration and re-platforming of AI/ML and statistical models, troubleshooting discrepancies in data, code logic, and performance
Partner with data engineering, analytics, and business teams to maintain continuity of business-critical reporting during migration
Build automated testing, monitoring, and validation processes to ensure long-term data and model integrity
Document migration processes, code changes, and best practices, and contribute to ongoing optimization of analytics workflows in the cloud
The Offer
You will receive the following benefits:
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
