Analytics Engineer/GCP/Chicago LOCAL
Indexed description
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 Bitquery
- 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
- 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
- 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
- Bonus eligible
- Medical, Dental, and Vision Insurance
- Vacation Time
- Stock Options
Posted By: McIver Harris
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