Cloud Data Engineer

Key Responsibilities:

• Design and develop scalable ETL/ELT pipelines using Dataflow, Dataproc, Apache Beam, Cloud Composer (Airflow), and other GCP services.
• Build and maintain data lakes and data warehouses using BigQuery, Cloud Storage, and Cloud SQL/Spanner.
• Implement and optimize data ingestion from a variety of structured and unstructured sources using GCP-native tools and APIs.
• Work with Pub/Sub, Cloud Functions, and Eventarc for real-time data processing and streaming pipelines.
• Ensure data governance, quality, and security using best practices for IAM, encryption, data cataloging, and auditing.
• Collaborate with stakeholders to gather requirements, define data models, and deliver insights via BI tools.
• Automate workflows and monitoring using tools like Cloud Monitoring, Logging, and Terraform or Deployment Manager.
• Stay current with the latest GCP tools, features, and trends in cloud data engineering.

Qualifications and Requirements:

• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 3+ years of experience in data engineering, including at least 1–2 years on Google Cloud Platform.
• Proficiency with SQL, Python, and/or Java for data processing and scripting.
• Hands-on experience with GCP services like:
• BigQuery
• Cloud Storage
• Dataflow / Dataproc
• Pub/Sub
• Composer
• Cloud Functions
• Solid understanding of data modeling, partitioning, performance tuning, and schema design.
• Experience with DevOps practices and CI/CD pipelines for data projects.