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Design, develop, and optimize data models and datasets in Google BigQuery
Write and optimize complex SQL queries, views, and stored procedures in BigQuery
Build and maintain ETL/ELT pipelines using GCP services
Ingest and process large-scale structured and semi-structured data
Implement data transformations using BigQuery SQL and cloud-based data processing tools
Optimize query performance and cost using partitioning, clustering, and query optimization techniques
Integrate data from various sources including cloud storage, databases, APIs, and streaming sources
Work with Cloud Storage, Dataflow, Dataproc, or similar services
Ensure data quality, consistency, and reliability
Collaborate with BI, analytics, and business teams to meet data requirements
Support CI/CD, deployment, and monitoring of data pipelines
GCP certifications (Professional Data Engineer / Associate Data Engineer)
Experience with Looker, Data Studio, or other BI tools
Agile/Scrum working experience
5-9 years of overall experience in data engineering / analytics engineering
3+ years of hands-on experience with GCP BigQuery
Strong proficiency in SQL (BigQuery dialect preferred)
Experience with Google Cloud Platform (GCP) services, such as:
BigQuery
Cloud Storage
Dataflow / Dataproc (good to have)
Solid understanding of data warehousing and analytics concepts
Experience with batch and near real-time data processing
Familiarity with data modeling techniques and large-scale datasets
Experience with Python or Shell scripting (preferred)
Knowledge of Git and CI/CD practices
Strong analytical, debugging, and communication skills
We are seeking an experienced GCP BigQuery Developer / Data Engineer to design, develop, and manage scalable analytics and data solutions on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in BigQuery, SQL, and cloud-native data engineering services to support enterprise analytics, reporting, and data science initiatives.
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