GCP Data Engineer: Face To Face Hackathon on 26-Sep in Bangalore

Hi

We are conducting Face to Face Hackathonon 26-Sep i.e on Saturday in Bangalore, Jigni Office.

Position: GCP Data Engineer

Experience: 5+ Years
Location: Bangalore
Employment Type: Full-Time

Job Summary

We are seeking an experienced GCP Data Engineer with 5+ years of experience in designing, developing, and optimizing scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong expertise in Google Cloud Platform (GCP), BigQuery, PySpark, Dataproc, DBT, and Python to support enterprise data warehousing, analytics, and reporting initiatives.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform.
• Develop and optimize data transformation workflows using DBT and BigQuery.
• Build and manage large-scale batch and streaming data processing solutions using PySpark and Dataproc.
• Design and implement data models, partitioning, clustering, and performance tuning strategies in BigQuery.
• Develop reusable and efficient Python-based data engineering frameworks.
• Integrate data from multiple sources, ensuring data quality, consistency, and governance.
• Monitor, troubleshoot, and optimize existing data pipelines and workflows.
• Collaborate with Data Analysts, Data Scientists, and business stakeholders to understand data requirements.
• Implement CI/CD processes and automation for data engineering solutions.
• Ensure adherence to data security, compliance, and best practices.

Required Skills

• 5+ years of experience in Data Engineering and ETL Development.
• Strong hands-on experience with:
• Google BigQuery
• DBT (Data Build Tool)
• PySpark
• Google Cloud Dataproc
• Python
• Good knowledge of SQL and query optimization techniques.
• Experience in designing data warehouses and dimensional data models.
• Hands-on experience with GCP services such as:
• Cloud Storage
• Cloud Composer
• Pub/Sub
• Dataflow (preferred)
• IAM
• Experience with source control tools such as Git.
• Understanding of data governance, data quality, and security best practices.