Design, develop, and maintain data warehouses using Google BigQuery.
Build and optimize ETL/ELT pipelines for large-scale data processing.
Develop and maintain data models, schemas, and partitioning strategies.
Write and optimize complex SQL queries for analysis and reporting.
Integrate data from multiple sources using GCP services such as Dataflow, Cloud Storage, Pub/Sub, and Dataproc.
Monitor data quality, performance, and security standards.
Implement data governance and compliance best practices.
Collaborate with data analysts, business stakeholders, and application teams to understand data requirements.
Troubleshoot and resolve performance bottlenecks in BigQuery workloads.
Support reporting and visualization tools such as Looker, Tableau, or Power BI.
Required Skills
Technical Skills
Solid experience with Google BigQuery.
Advanced SQL programming and query optimization.
Experience with Google Cloud Platform (GCP) services.
Knowledge of data warehousing concepts and dimensional modeling.
Hands-on experience with ETL/ELT tools and frameworks.
Proficiency in Python, Scala, or Java for data engineering tasks.
Experience with data orchestration tools such as Airflow or Cloud Composer.
Understanding of data security, IAM, and access controls in GCP.
Knowledge of Git and CI/CD practices.
Preferred Skills
Experience with Dataflow, Dataproc, Pub/Sub, Cloud Functions, and Cloud Storage.
Experience with Looker, Tableau, or Power BI.
Familiarity with Spark and distributed data processing.
Knowledge of DevOps and Infrastructure as Code (Terraform).