GCP Data Engineer

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Role Summary

GCP Data Engineer

Google Cloud Platform (GCP)

Key Responsibilities

• Design and develop production-grade data engineering solutions using GCP services such as:
• BigQuery, Dataflow, Dataform, Dataproc, Cloud Composer, Cloud SQL, Airflow, Compute Engine, Cloud Functions, Cloud Run, Cloud Build, Pub/Sub, App Engine
• Develop batch and real-time streaming pipelines for data ingestion, transformation, and processing.
• Integrate data from multiple sources including legacy and cloud-based systems.
• Collaborate with stakeholders and product teams to gather data requirements and align technical solutions to business needs.
• Conduct in-depth data analysis and impact assessments for data migrations and transformations.
• Implement CI/CD pipelines using tools like Tekton, Terraform, and GitHub.
• Optimize data workflows for performance, scalability, and cost-effectiveness.
• Lead and mentor junior engineers; contribute to knowledge sharing and documentation.
• Champion data governance, data quality, security, and compliance best practices.
• Utilize monitoring/logging tools to proactively address system issues.
• Deliver high-quality code using Agile methodologies including TDD and pair programming.
  

Required Skills & Experience

• GCP Data Engineer Certification.
• Minimum 5+ years of experience designing and implementing complex data pipelines.
• 3+ years of hands-on experience with GCP.
• Strong expertise in:
• SQL, Python, Java, or Apache Beam
• Airflow, Dataflow, Dataproc, Dataform, Data Fusion, BigQuery, Cloud SQL, Pub/Sub
• Infrastructure-as-Code tools such as Terraform
• DevOps tools: GitHub, Tekton, Docker
• Solid understanding of microservice architecture, CI/CD integration, and container orchestration.
• Experience with data security, governance, and compliance in cloud environments.
  

Preferred Qualifications

• Experience with real-time data streaming using Apache Kafka or Pub/Sub.
• Exposure to AI/ML tools or integration with AI/ML pipelines.
• Working knowledge of data science principles applied on large datasets.
• Experience in a regulated domain (e.g., financial services or insurance).
• Experience with project management and agile tools (e.g., JIRA, Confluence).
• Strong analytical and problem-solving mindset.
• Effective communication skills and ability to collaborate with cross-functional teams.
  

Education

• Required: Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Preferred: Master's degree or certifications in relevant domains.