Gcp Data Engineer

Role & responsibilities

• Expert-level knowledge of Google Cloud Platform services including:
• BigQuery advanced SQL, partitioning, optimization, and cost control
• Dataflow (Apache Beam) – large-scale batch and streaming data pipelines
• Dataproc – Spark and Hadoop-based distributed processing
• Cloud Composer (Airflow) – workflow orchestration, scheduling, and dependency management
• Pub/Sub – event-driven, real-time ingestion
• Cloud Storage (GCS) – data lake setup, lifecycle management, access control
• Strong proficiency in Python (Pandas, PySpark, Beam SDK) and SQL for data wrangling and transformation.
• Expertise in ETL/ELT design, data lake/data warehouse/lakehouse architecture.
• Experience with DevOps & CI/CD using tools such as GitHub Actions, Jenkins, or Cloud Build.
• Hands-on with Terraform or Deployment Manager for Infrastructure as Code (IaC).
• Solid understanding of GCP IAM, VPC, security policies, and encryption mechanisms.
• Familiarity with data quality, metadata, lineage, and cataloging tools (e.g., Data Catalog).
• Proficiency in cost governance, performance tuning, and resource monitoring (Cloud Monitoring/Logging).
• Knowledge of modern data frameworks and data integration between systems like Kafka, Snowflake, or Looker.