GCP BigQuery

Data Warehousing & Big Query Development:

Design and implement data warehouse solutions using Google Big Query
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 Big Query 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 Big Query, 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 / Big Query development
Strong expertise in SQL (mandatory)

Hands-on experience with Google Big Query:

Experience with data modeling (star/snowflake schemas)

GCP Tools & Services:

Big Query
Cloud Storage
Dataflow / Dataproc
Pub/Sub
Cloud Composer (Airflow)

Programming Skills:

Proficiency in Python / SQL scripting
Experience with Spark (Py Spark) is a plus

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

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)

Education: MCA,MSc,MTech,Bachelor of Engineering,BCA,BSc,BTech

• Preferred skills: Technology->Cloud Platform->GCP Core Services->GCP,Technology->Open System->Python
• Open System