Description

Design and implement large-scale data solutions on Google Cloud Platform.

This role is on-site.

Responsibilities

• Design scalable data solutions using GCP services to ensure performance and reliability.
• Automate infrastructure provisioning and management using Terraform.
• Build and deploy end-to-end machine learning pipelines and production models.
• Develop data integration, transformation, and processing workflows.
• Manage data orchestration and CI/CD pipelines for data engineering workflows.

Required Skills

• 9+ years of experience in data engineering with a focus on GCP, Azure, or AWS.
• Strong proficiency in Python programming.
• Hands-on experience with BigQuery, BigTable, and Google Cloud Storage.
• Expertise in data processing tools including Dataflow, Dataproc, and Cloud Composer/Airflow.
• Experience with infrastructure as code using Terraform.
• Proficiency in big data technologies such as Spark, PySpark, Scala, Hive, Sqoop, and HDFS.
• Experience with CI/CD tools like Tekton and Cloud Build.
• Knowledge of GCP services including PubSub, Data Fusion, and Vertex AI.
• Experience building ML pipelines using TensorFlow, PyTorch, or Scikit-learn.

Preferred Skills

• Experience with large-scale distributed systems and data warehousing.
• Familiarity with cloud-native security best practices.

Key Skills

Education

Not specified