Data Warehousing & BigQuery Development
Design and implement data warehouse solutions using Google BigQuery
Develop, optimize, and maintain complex SQL queries and data models
Create efficient partitioning, clustering, and indexing strategies
Data Pipeline Development
Build scalable data pipelines using GCP services (Dataflow, Dataproc, Cloud Composer)
Perform data ingestion from various sources (APIs, databases, cloud storage)
Ensure data transformation, cleansing, and validation
Performance Optimization
Optimize BigQuery queries for cost and performance
Monitor query execution and tune workloads
Implement best practices for storage and compute efficiency
Integration & ETL/ELT
Implement ETL/ELT workflows using BigQuery, Cloud Storage, Pub/Sub
Integrate data from multiple cloud and on-prem systems
Automate workflows and scheduling
Collaboration & Reporting
Work closely with data analysts, data scientists, and business teams
Support reporting tools like Looker, Data Studio (Looker Studio), Tableau
Translate business requirements into scalable data solutions
Required Skills & Qualifications
Core Technical Skills
3-5 years of experience in data engineering / BigQuery development
Strong expertise in SQL (mandatory)
Hands-on experience with Google BigQuery
Experience with data modeling (star/snowflake schemas)
GCP Tools & Services
BigQuery
Cloud Storage
Dataflow / Dataproc
Pub/Sub
Cloud Composer (Airflow)
Programming Skills
Proficiency in Python / SQL scripting
Experience with Spark (PySpark) is a plus

Experience with real-time data streaming
Knowledge of data governance, security, and IAM in GCP
Familiarity with CI/CD pipelines and DevOps practices
Certification in Google Cloud (e.g., Data Engineer Associate/Professional)

* Primary skills:Technology->Cloud Platform->GCP, BIG QUERY