GCP BigQuery Data Engineer

Job Title: GCP BigQuery Data Engineer Location: Santa Clara, CA (100 % Onsite) Duration: 6 + Months (Contract) Position Overview We’re seeking a highly skilled GCP BigQuery Data Engineer to design, optimize, and scale data pipelines in a petabyte-scale analytics environment. This role demands deep expertise in Google BigQuery, Python, and SQL, plus strong experience with Airflow / Cloud Composer / Dagster for orchestration and performance tuning. You’ll work with cross-functional data teams to model data, automate workflows, and enhance performance in complex cloud environments. Key Responsibilities • Design and implement efficient data pipelines and ETL/ELT processes in GCP (BigQuery, Data Lake, Storage Buckets). • Develop and optimize data models for large-scale analytical workloads. • Write, tune, and maintain complex SQL queries and Python scripts for data transformation. • Perform performance tuning and query optimization within petabyte-scale BigQuery environments. • Build and manage workflow orchestration using Airflow, Cloud Composer, or Dagster. • Collaborate with analysts, data scientists, and stakeholders to align data architecture with business goals. • Apply CI/CD best practices and use GitHub for version control and deployment. • Monitor, troubleshoot, and enhance pipeline reliability and scalability. Required Skills & Experience • 4 – 7 years in data engineering or analytics. • Strong proficiency in GCP BigQuery and SQL (advanced query optimization). • Experience in Python programming and data modeling. • Solid knowledge of ETL tools and pipeline orchestration frameworks (Airflow, Cloud Composer, Dagster). • Experience with performance tuning, data standardization, and metric governance in large-scale systems. • Familiarity with CI/CD pipelines and GitHub workflows. • Understanding of Snowflake or similar cloud-data warehousing tools is a plus. Preferred Skills • Experience building pipelines across multi-cloud environments. • Exposure to Data Governance / Security frameworks (RBAC, data lineage, metadata management). • Hands-on experience with containerization and DevOps concepts. Education • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related discipline.