GCP Data Engineer

Job Summary:

We are looking for a skilled GCP Data Engineer to design, build, and optimize scalable data pipelines and architectures on Google Cloud Platform (GCP). The ideal candidate will have expertise in BigQuery, Dataflow, Pub/Sub, Cloud Storage, and other GCP services to develop robust data solutions that drive business insights.

Key Responsibilities:

• Design and develop ETL/ELT pipelines to process large-scale structured and unstructured data.
• Implement data ingestion, transformation, and storage solutions using BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
• Optimize and monitor data workflows and pipelines for performance, scalability, and cost-efficiency.
• Work with data modeling and warehouse concepts to structure data for analytical purposes.
• Collaborate with Data Scientists, Analysts, and Software Engineers to ensure seamless data integration.
• Implement data security, governance, and compliance best practices in accordance with industry standards.
• Automate infrastructure provisioning and deployment using Terraform, Cloud Composer (Apache Airflow), or CI/CD tools.
• Troubleshoot and resolve data pipeline failures and performance bottlenecks.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• 2+ years of experience working with GCP data engineering tools.
• Strong expertise in SQL, Python, or Java for data processing.
• Hands-on experience with Google BigQuery, Dataflow, Pub/Sub, Cloud Functions, and Cloud Storage.
• Knowledge of Apache Beam, Spark, or Kafka for streaming and batch processing.
• Experience with Airflow (Cloud Composer) for orchestration.
• Familiarity with Terraform, Kubernetes, and CI/CD pipelines for automation.
• Understanding of data governance, security, and compliance (GDPR, HIPAA, etc.).
• Excellent problem-solving and communication skills.

Preferred Qualifications:

• GCP certifications like Professional Data Engineer or Associate Cloud Engineer.
• Experience with machine learning pipelines and MLOps in GCP.
• Knowledge of other cloud platforms (AWS/Azure) and hybrid cloud solutions.
• Exposure to Looker, Data Studio, or other BI tools for analytics.