Overview
On Site
Depends on Experience
Contract - W2
Contract - Independent
Contract - 6 month(s)
No Travel Required
Skills
Data Architect
ETL
Data Modeling
data pipelines
Data Engg
Data design
Machine learning models
Job Details
Job Description: Google Cloud Platform Data Engineering Architect Lead (with Machine Learning Expertise)
Location: Chicago, IL
Employment Type: Full-time onsite 5 days
About the Role
We are seeking a highly skilled Data Engineering Architect Lead with deep expertise in Google Cloud Platform (Google Cloud Platform) and strong experience in Machine Learning (ML).
Location: Chicago, IL
Employment Type: Full-time onsite 5 days
About the Role
We are seeking a highly skilled Data Engineering Architect Lead with deep expertise in Google Cloud Platform (Google Cloud Platform) and strong experience in Machine Learning (ML).
This role will lead the design, development, and optimization of enterprise-scale data solutions, ensuring robust architecture, scalability, and actionable insights for business and technical stakeholders.
Key Responsibilities
• Lead the architecture and implementation of data pipelines, warehouses, and lakes on Google Cloud Platform.
• Design and optimize ETL/ELT workflows using tools such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
• Collaborate with data scientists to operationalize ML models and integrate them into production systems.
• Define and enforce data governance, security, and compliance standards.
• Provide technical leadership and mentorship to data engineers and analysts.
• Partner with business stakeholders to translate requirements into scalable data solutions.
• Drive performance tuning, cost optimization, and reliability improvements across Google Cloud Platform environments.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 8+ years of experience in data engineering and architecture, with at least 3+ years in a leadership role.
• Proven expertise in Google Cloud Platform services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer).
• Strong knowledge of data modeling, distributed systems, and real-time streaming architectures.
• Hands-on experience deploying and scaling Machine Learning models in production.
• Proficiency in Python, SQL, and Java/Scala.
• Experience with CI/CD pipelines, MLOps frameworks, and containerization (Docker/Kubernetes).
• Excellent communication and leadership skills to engage both technical and non-technical stakeholders.
Preferred Qualifications
• Google Cloud Platform Professional Data Engineer or Architect certification.
• Experience with TensorFlow, PyTorch, or Vertex AI.
• Background in enterprise-scale data migration and modernization projects.
• Familiarity with data governance tools and metadata management frameworks.
Key Responsibilities
• Lead the architecture and implementation of data pipelines, warehouses, and lakes on Google Cloud Platform.
• Design and optimize ETL/ELT workflows using tools such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
• Collaborate with data scientists to operationalize ML models and integrate them into production systems.
• Define and enforce data governance, security, and compliance standards.
• Provide technical leadership and mentorship to data engineers and analysts.
• Partner with business stakeholders to translate requirements into scalable data solutions.
• Drive performance tuning, cost optimization, and reliability improvements across Google Cloud Platform environments.
Required Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 8+ years of experience in data engineering and architecture, with at least 3+ years in a leadership role.
• Proven expertise in Google Cloud Platform services (BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer).
• Strong knowledge of data modeling, distributed systems, and real-time streaming architectures.
• Hands-on experience deploying and scaling Machine Learning models in production.
• Proficiency in Python, SQL, and Java/Scala.
• Experience with CI/CD pipelines, MLOps frameworks, and containerization (Docker/Kubernetes).
• Excellent communication and leadership skills to engage both technical and non-technical stakeholders.
Preferred Qualifications
• Google Cloud Platform Professional Data Engineer or Architect certification.
• Experience with TensorFlow, PyTorch, or Vertex AI.
• Background in enterprise-scale data migration and modernization projects.
• Familiarity with data governance tools and metadata management frameworks.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.