Bigquery Engineer

Role : Google Cloud Platform Data Engineer
Location : Charlotte NC (onsite)

We are seeking a highly skilled Google Cloud Platform Data Engineer to design, build, and optimize robust data pipelines. In this role, you will bridge the gap between our NoSQL data sources (MongoDB) and our analytical data warehouse (Big Query). You will be responsible for end-to-end data integration, performance tuning, and providing production support and debugging to ensure high availability and data quality.

• Pipeline Integration: Design, build, and deploy scalable ETL/ELT data pipelines using Python and Google Cloud Platform-native services.
• Database Management: Integrate data from MongoDB into Google Cloud Storage and load/transform it in Big Query for analytics.
• Support & Debugging: Monitor, troubleshoot, and resolve pipeline failures and data discrepancies.
• Performance Tuning: Optimize Big Query queries, Dataflow jobs, and MongoDB indexing to ensure cost-efficiency and fast execution.
• Collaboration: Partner with Data Scientists, Software Engineers, and business stakeholders to translate requirements into reliable data models.

• Education: Bachelor's degree in computer science, Engineering, or a related technical field.
• Core Google Cloud Platform: Hands-on experience with core Google Cloud Platform data services: Big Query, Cloud Dataflow, Cloud Composer (Airflow), and Cloud Storage.
• Databases: Strong proficiency in NoSQL databases (specifically MongoDB ) and data warehousing concepts.
• Programming: Advanced programming and scripting skills in Python and complex SQL.
• Support & CI/CD: Experience utilizing Cloud Logging/Monitoring for root cause analysis and implementing CI/CD frameworks.

• Certifications such as the Google Cloud Professional Data Engineer.
• Familiarity with the BigQuery Data Engineering Agent to aid in pipeline troubleshooting and generation.

For applications and inquiries,