Responsibilities:
- Design, optimize, and maintain scalable data solutions using Google Cloud Platform, with a strong focus on BigQuery.
- Analyze and improve BigQuery query performance, ensuring efficient execution and reduced processing costs.
- Implement best practices for BigQuery architecture, including partitioning, clustering, table design, and data lifecycle management.
- Develop and optimize complex SQL queries for analytical and reporting workloads.
- Monitor query performance, troubleshoot bottlenecks, and provide performance tuning recommendations.
- Collaborate with Data Engineers, Analysts, and business stakeholders to understand data requirements and deliver scalable solutions.
- Design and maintain ETL/ELT pipelines using GCP services such as Dataflow, Pub/Sub, and Google Cloud Storage.
- Create automation scripts using Python or similar programming languages for reporting, monitoring, and optimization tasks.
- Manage and optimize BigQuery costs by analyzing usage patterns and implementing cost-efficient strategies.
- Utilize GCP monitoring and logging tools to track system health, resource utilization, and query performance.
- Define and document best practices, standards, and optimization guidelines for BigQuery and GCP environments.
- Support data modeling activities for analytical and business intelligence solutions.
- Stay updated with new GCP and BigQuery features, industry trends, and cloud optimization techniques.
Qualifications:
- Strong hands-on experience with Google Cloud Platform (GCP), especially BigQuery.
- In-depth understanding of BigQuery architecture, storage, partitioning, clustering, materialized views, and query optimization techniques.
- Advanced SQL knowledge with proven experience writing and optimizing complex queries.
- Experience analyzing query execution plans and identifying performance bottlenecks.
- Solid understanding of BigQuery pricing models, cost optimization strategies, and resource management.
- Experience designing and implementing ETL/ELT pipelines in cloud environments.
- Knowledge of GCP services such as Google Cloud Storage, Dataflow, Pub/Sub, and their integration with BigQuery.
- Strong data modeling skills for analytical and reporting solutions.
- Experience with monitoring and observability tools such as Cloud Monitoring and Log Analysis.
- Proficiency in Python or similar scripting languages for automation and operational improvements.
- Ability to benchmark system performance and recommend scalability improvements.
- Strong communication and stakeholder management skills.
- Experience creating technical documentation, standards, and operational guidelines.
- Ability to work collaboratively in cross-functional and Agile environments.
- Continuous learning mindset with interest in staying current on GCP and cloud data technologies.
*We are an equal opportunity employer and value diversity. All employment decisions are made without regard to age, gender, disability, race, ethnicity, religion, sexual orientation, or any other protected characteristic. We encourage applicants from all backgrounds to apply.*