GCP Data Architect

Job Overview

We are looking for an experienced Microsoft Azure to Google Cloud Platform (GCP) migration Data Engineer to design, build, and optimize scalable data pipelines, data lakes, and analytics solutions on GCP.
The role requires strong experience with cloud native data engineering tools such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and GCS, along with excellent ETL/ELT design and performance tuning capabilities.

Key Responsibilities

Data Pipeline Design & Development

• Build scalable ETL/ELT pipelines using GCP services (Dataflow, Dataproc, BigQuery).
• Develop data ingestion frameworks for structured, semi structured, and unstructured data.
• Implement streaming pipelines using Pub/Sub + Dataflow.
  
  

Cloud Architecture & Data Modeling

• Design data lake and warehouse solutions using GCS, BigQuery, Dataproc.
• Design star/snowflake schemas, partitioning, clustering, and query optimization.
  
  

Orchestration & Automation

• Build workflow orchestration using Cloud Composer (Airflow) or Databricks Workflows.
• Candidate should have hands on experience on writing sql query, store procedure and python language.
• Create reusable job templates, automation scripts, CI/CD pipelines.
  
  

Data Quality, Security & Governance

• Implement data validation, data quality rules, and monitoring dashboards.
• Dataplex for data quality and governance
• Ensure compliance with GDPR, internal audit, and data privacy requirements.
  
  

Performance Optimization

• Optimize BigQuery queries (partition, cluster, materialized views).
• Tune Dataflow pipelines for cost and performance efficiency.
  
  

Cross Functional Collaboration

• Work with data architects, analysts, product teams, and business users.
• Understand business requirements and translate them into technical solutions.