GCP BQ/ GCP python

GCP Big Query Development:

Design, develop, and optimize data warehouses using Google Big Query
Build and maintain data models (fact/dimension, star/snowflake schemas)
Develop complex SQL queries for analytics and reporting
Optimize queries for cost, performance, and scalability
Implement partitioning, clustering, and materialized views

Python Development

Develop data pipelines and workflows using Python
Build reusable scripts for data ingestion, transformation, and automation
Integrate Python applications with GCP services and APIs
Ensure code quality, modularity, and scalability

Data Engineering & ETL:

Design and build ETL/ELT pipelines using GCP tools
Ingest data from multiple sources (APIs, databases, streaming platforms)
Process structured and unstructured data efficiently
Ensure data quality, validation, and governance

GCP Cloud Services:

Work with GCP services such as:

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

Design scalable and secure cloud-native architectures

Performance Optimization

Monitor and optimize Big Query cost and performance
Troubleshoot data pipeline failures and bottlenecks
Implement best practices for efficient data processing

Collaboration & Leadership:

Collaborate with data scientists, analysts, and business stakeholders
Provide technical guidance and mentorship to junior engineers
Participate in architecture and design discussions
Work in Agile/Scrum environments

• Primary skills:Technology->Functional Testing->Mainframe testing->Proterm,Technology->Open System->Python
• Open System

Required Skills & Qualifications:

✅ Core Skills

5–9 years of experience in data engineering / big data development
Strong hands-on experience with GCP Big Query (mandatory)
Strong proficiency in Python (mandatory)
Expertise in SQL and query optimization
Experience in building ETL/ELT pipelines

✅ Technical Skills

Deep knowledge of Big Query architecture and data modeling
Experience with Airflow / Cloud Composer for orchestration
Strong understanding of data warehousing concepts
Familiarity with Git and CI/CD processes

Knowledge of REST APIs and integrations:

Preferred Skills:

Experience with streaming (Pub/Sub, Kafka equivalent)
Exposure to Dataproc / Spark / Py Spark
Familiarity with data lakes and lakehouse architectures
Knowledge of Docker/Kubernetes
Experience with BI tools (Looker, Tableau, Power BI)

Education: MCA,MSc,MTech,BCA,BSc,BTech

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