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.

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.

Google Cloud Data Engineer