Job Summary :

We are looking for a skilled GCP Data Engineer with hands-on experience in designing, developing, and managing scalable data pipelines and cloud-based data platforms on Google Cloud Platform (GCP).

The ideal candidate will have expertise in PySpark, Dataproc, SQL, and BigQuery, and will work closely with business stakeholders, data scientists, and engineering teams to build high-performance data solutions.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on Google Cloud Platform (GCP).

- Build and optimize data processing solutions using PySpark and Dataproc.

- Develop, manage, and optimize BigQuery datasets, tables, and queries for analytics and reporting.

- Integrate data from multiple structured and unstructured data sources.

- Ensure data quality, integrity, security, and governance across the data platform.

- Optimize data processing performance and cloud resource utilization.

- Collaborate with cross-functional teams to understand business requirements and deliver scalable data solutions.

- Monitor, troubleshoot, and resolve data pipeline and production issues.

- Participate in code reviews, testing, deployment, and CI/CD processes.

- Document data architectures, workflows, and technical solutions.

Required Skills:

- 8-15 years of experience in Data Engineering.

- Strong expertise in Google Cloud Platform (GCP).

- Hands-on experience with PySpark for large-scale data processing.

- Experience with Google Cloud Dataproc.

- Strong proficiency in SQL and query optimization.

- Expertise in BigQuery for data warehousing and analytics.

- Experience in developing ETL/ELT pipelines and cloud-native data architectures.

- Knowledge of Git, CI/CD pipelines, and cloud deployment practices.

- Strong analytical, problem-solving, and communication skills.

Preferred Skills :

- Experience with Apache Airflow or Cloud Composer for workflow orchestration.

- Knowledge of Kafka or Pub/Sub for streaming data pipelines.

- Familiarity with Python and cloud automation.

- Experience with data lakes, data warehousing, and modern analytics platforms.

- Google Cloud Professional Data Engineer certification is an added advantage.

- Experience working in Agile/Scrum environments.