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