GCP Data Engineer

Job description
Role: GCP Data Engineer
Experience: 6-10 Years
Locations: Bengaluru, Hyderabad, Kolkata
Job Requirements
We are seeking an experienced GCP Data Engineer to design, develop, and maintain scalable data solutions on the Google Cloud Platform (GCP). The ideal candidate will have strong expertise in building modern data pipelines, data warehousing, big data processing, and cloud-native analytics solutions. The role requires close collaboration with business stakeholders, data architects, data scientists, and application teams to deliver reliable and high-performance data platforms.
Key Responsibilities*
Design, develop, and optimize scalable data pipelines using GCP services.
Build and maintain batch and real-time data ingestion and processing frameworks.
Develop enterprise-grade data warehousing solutions using BigQuery.
Implement ETL/ELT processes for structured and unstructured data.
Integrate data from multiple sources including databases, APIs, files, and streaming platforms.
Ensure data quality, governance, security, and compliance across data platforms.
Optimize query performance, storage, and processing costs within GCP.
Automate deployment and operational processes using CI/CD and Infrastructure as Code (IaC).
Monitor data pipelines and troubleshoot production issues.
Collaborate with Data Architects, Business Analysts, and Data Scientists to translate business requirements into technical solutions.
Implement data models, metadata management, and data lineage best practices.
Support migration of on-premise or multi-cloud data platforms to GCP.
Mentor junior engineers and participate in technical design reviews.
Required Technical Skills
Google Cloud Storage (GCS)
BigQuery
Cloud Composer (Apache Airflow)
Dataflow
Dataproc
Pub/Sub
Cloud Functions
Cloud Run
Cloud SQL
BigLake (preferred)
Vertex AI integration (good to have)
Python
SQL (Advanced)
PySpark
Education Requirements
Bachelor's/Master’s in Computer Science or equivalent (Preferred)
Certifications
GCP Cloud Data Engineer (Preferred)

Work arrangement
Hybrid