Job Title: Data Engineer – GCP, PySpark & Scala

We are looking for an experienced Data Engineer with 6+ years of experience in designing, developing, and maintaining scalable data engineering solutions on the Google Cloud Platform (GCP). The ideal candidate should have solid hands-on expertise in PySpark, Scala, Airflow, BigQuery (BQ), Dataproc, and ETL development.

The candidate will be responsible for developing, deploying, monitoring, and optimizing batch ETL workflows in GCP settings. You should have experience building high-performance, reliable, and scalable data pipelines using PySpark and Scala, while leveraging Airflow for workflow orchestration, dependency management, scheduling, and idempotent execution.

A robust understanding of Medallion Architecture (Bronze, Silver, Gold layers) is required, along with experience implementing data quality checks, data validation, summarization, and transformation processes. The role also requires expertise in performance tuning and optimization of ETL jobs, improving pipeline efficiency,



and implementing observability solutions for proactive monitoring. Experience creating operational runbooks and supporting continuous optimization initiatives is highly desirable.

The ideal candidate should be proficient in BigQuery, Dataproc, and other GCP services, with the ability to troubleshoot production issues and ensure high data reliability. Knowledge of data governance principles, metadata management, and best practices for secure and compliant data processing will be an added advantage.

Mandatory Skills

6+ years of Data Engineering experience
Google Cloud Platform (GCP)
PySpark
Scala
Apache Airflow
BigQuery (BQ)
Dataproc
ETL Development
Medallion Architecture
Data Quality & Validation
Performance Optimization
Observability
Runbook Creation

Good To Have

Data Governance
Metadata Management
Production Support and Monitoring

Skills: airflow,data,gcp,medallion

📌 Data Engineer Gcp Gurugram
🏢 Zorba AI
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