Raas Infotek Corporation
GCP Data Engineer with AI and ML Job Description:
We are hiring a GCP Data Engineer with AI and ML experience for a full-time onsite position in San Jose, California. The ideal candidate will have a minimum of 10 years of experience in data engineering and a strong understanding of machine learning workflows. This role is focused on building scalable, efficient, and secure data pipelines on the Google Cloud Platform (GCP) to support advanced AI and ML applications.
As a GCP Data Engineer, you will work closely with Data Scientists and Machine Learning Engineers to deliver clean, curated, and real-time data that drives intelligent insights and automated decisions. You will be responsible for optimizing end-to-end data workflows, enhancing data accessibility and quality, and leveraging tools such as BigQuery, Dataflow, Vertex AI, and Cloud Composer.
Key Responsibilities for GCP Data Engineer with AI and ML:
-
Design and develop ETL and ELT pipelines for batch and real-time data processing using GCP tools such as Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
-
Prepare, transform, and curate large-scale structured and unstructured datasets for AI and ML workloads in collaboration with data science teams.
-
Leverage GCP services including BigQuery, Cloud Storage, Cloud SQL, and Bigtable for scalable data warehousing and storage.
-
Implement MLOps practices and work with Vertex AI, AutoML, and AI Platform for model deployment and monitoring.
-
Ensure data quality, integrity, and governance through proper validation, security policies, and compliance standards.
-
Monitor and optimize the performance and cost of data pipelines, storage, and compute resources.
-
Develop CI/CD workflows for continuous delivery and integration of data and ML pipelines.
-
Collaborate with cross-functional teams including Software Engineers, Product Managers, and Business Analysts.
-
Stay current with GCP feature releases, AI and ML advancements, and data engineering trends to continually enhance infrastructure and capabilities.
Required Qualifications for GCP Data Engineer with AI and ML
-
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
-
Minimum 10 years of experience in data engineering, including at least 3 years in GCP environments.
-
Strong knowledge of GCP data tools including BigQuery, Dataflow, Dataproc, Cloud Composer, and Vertex AI.
-
Proficiency in Python for scripting and data manipulation. Experience with Scala or Java is a plus.
-
Expertise in SQL, relational and NoSQL databases, and data modeling.
-
Solid understanding of machine learning workflows such as data preprocessing, feature engineering, and model deployment.
-
Familiarity with TensorFlow, PyTorch, or other ML frameworks.
-
Strong experience with distributed systems and real-time data processing frameworks.
-
Hands-on knowledge of version control systems like Git and CI/CD tools.
-
Google Cloud Professional Data Engineer certification is highly preferred.
-
Strong problem-solving abilities and excellent communication skills.
Preferred Skills for GCP Data Engineer with AI and ML
-
Experience with AI infrastructure automation and orchestration tools.
-
Exposure to Apache Airflow, Kafka, or Spark.
-
Familiarity with DevOps practices for deploying machine learning models at scale.
-
Experience with large-scale data migration and transformation projects.
Why Join Us?
This is an exciting opportunity to work in a data-driven organization where machine learning and artificial intelligence are at the core of business innovation. You will have access to cutting-edge GCP tools, work with passionate experts, and make a measurable impact on AI-driven products.
-
Work in a highly collaborative and agile environment
-
Contribute to advanced AI initiatives that drive business growth
-
Learn and grow with continuous training and certification support
-
Competitive compensation and benefits package
Ready to Apply?
If you are a seasoned GCP Data Engineer with hands-on experience in AI and ML workflows, and ready to take on a challenging and rewarding role in San Jose, CA, we invite you to apply today. Join us and build the next generation of intelligent data systems.
Frequently Asked Questions (FAQs):
-
Is this a remote role?
No. This is a full-time onsite position located in San Jose, California. -
What level of experience is required?
A minimum of 10 years in data engineering is required, with hands-on experience in AI and ML projects. -
What cloud platform is used?
Google Cloud Platform (GCP) is the primary platform for all data and AI operations. -
Is certification in GCP mandatory?
It is not mandatory but Google Cloud Professional Data Engineer certification is strongly preferred. -
What programming languages should I know?
Proficiency in Python is essential. Experience with Java or Scala is a plus. -
Will I be working directly with Data Scientists?
Yes, close collaboration with Data Scientists and ML Engineers is part of the role. -
Which data processing tools are used?
Dataflow, Dataproc, Pub/Sub, and Cloud Composer are widely used. -
Do I need experience in MLOps?
Yes, you should be familiar with automating machine learning workflows and deployments. -
What ML tools will I work with?
You will work with Vertex AI, TensorFlow, Keras, PyTorch, and other AI services on GCP. -
What is the team structure?
The role involves working with cross-functional teams including engineers, analysts, and product managers. -
What types of datasets will I handle?
Structured, unstructured, and streaming data across multiple sources. -
Are performance monitoring and cost optimization part of the job?
Yes, continuous performance optimization and cost efficiency are key responsibilities. -
What database experience is required?
You should be experienced in SQL, BigQuery, Cloud SQL, and NoSQL databases like Bigtable. -
Will I need to build CI/CD pipelines?
Yes, you will develop and maintain CI/CD pipelines for data and ML workflows. -
When can I start?
Immediate joiners are preferred, but candidates with a standard notice period will also be considered.
Explore our Careers Page to see more job openings.
