Overview
On Site
Depends on Experience
Full Time
Skills
GCP
Data
BigQuery
Dataflow
Dataproc
Cloud Storage
Kubernetes Engine
ETL
Job Details
Role : Google Cloud Platform ML Architect -Data
Location : Chaska MN (100% onsite)
Hire type : FTE (No H1 Transfer)
- Detailed JD:
Responsible for designing, implementing, and managing data and machine learning solutions on Google Cloud Platform
Key Responsibilities:
- Design end-to-end data solutions, including data ingestion, storage, processing, and analysis pipelines, as well as machine learning model development, deployment, and monitoring pipelines.
- Design and implement scalable, secure, and cost-optimized cloud infrastructure using Google Cloud Platform services like BigQuery, Dataflow, Dataproc, Cloud Storage, and Kubernetes Engine.
- Design and implement data models, ensuring data consistency, accuracy, and accessibility for various applications and users.
- Establish MLOps practices, enabling the automation of machine learning model training, deployment, and monitoring.
- Ensure that all data solutions adhere to security and compliance standards, implementing access controls, encryption, and other security measures.
- Monitor and optimize the performance of data and machine learning systems, ensuring they meet business requirements and SLAs.
- Develop and implement strategies for managing and optimizing cloud costs, ensuring efficient resource utilization.
- They provide technical guidance and mentorship to other team members, fostering a culture of best practices and continuous improvement.
Key Skills:
- 10+ years of experience designing and developing production grade data architectures using google cloud data services and solutions
- Proficiency in BigQuery, Dataflow, Dataproc, Cloud Storage, pub-sub, Kubernetes Engine, and other relevant Google Cloud Platform services.
- Strong Experience with data warehousing, ETL processes, data modeling, and data pipeline development.
- Strong hands on experience in Python and SQL
- Strong experience of model development, deployment, and monitoring using Vertex AI
- Good experience of LLM, agents and agentic AI, Agent Space and hands on RAG experience
- Experience with cloud computing concepts, including infrastructure as code (IaC), scalability, security, and cost optimization.
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