Senior Google Cloud Data Analytics Support Engineer

About the Role

This role involves providing advanced L2/L3 technical assistance for Google Cloud Platform's (GCP) data analytics tools, including BigQuery, Dataflow, Cloud Composer using Airflow, Pub/Sub, Cloud Storage, and Looker Studio.

Key Responsibilities

• Deliver comprehensive support for GCP data analytics platforms, resolving complex production challenges through root cause analysis and corrective measures.
• Continuously monitor cloud environments with tools such as Cloud Logging, Cloud Monitoring, and tracing utilities to maintain service reliability and optimize performance.
• Tackle issues related to data pipelines, including failures, performance bottlenecks, latency, and quota constraints.
• Lead incident management processes including issue triage, communication with stakeholders, resolution, and conducting post-incident evaluations.
• Enhance BigQuery workloads' efficiency by applying query optimization, partitioning, clustering, and other performance tuning strategies.
• Work collaboratively with engineering teams and customers to reproduce problems, verify solutions, and ensure smooth deployment of fixes.
• Administer GCP services covering IAM roles, VPC setup, cloud storage, networking, and project configurations.
• Utilize programming skills in Python, SQL, and Shell scripting to automate, troubleshoot, and improve operational workflows.
• Maintain comprehensive documentation, including troubleshooting guides, knowledge base articles, RCAs, and support procedures for 24x7 cloud operations executed in rotations.

Candidate Profile

• Has 4 to 7 years of practical experience working with Google Cloud Platform, with deep knowledge of BigQuery, Dataflow, Airflow (Cloud Composer), Pub/Sub, Cloud Storage, and Looker Studio.
• Hands-on background in production support, incident handling, troubleshooting, and root cause analysis across large scale cloud infrastructure.
• Proven ability to tune BigQuery workloads, optimize SQL queries, and manage partitions and clustering for improved performance.
• Experience in managing and diagnosing complex data pipelines and distributed cloud applications.
• Strong scripting and automation skills using Python, SQL, and Shell script to facilitate operational excellence.
• Good understanding of GCP infrastructure components such as IAM, VPC, networking, storage, quotas, and project administration.
• Familiarity with cloud observability tools including Cloud Logging, Cloud Monitoring, and Cloud Trace aligning with best practices.
• Knowledge of CI/CD processes, version control with Git, and infrastructure as code principles for effective deployment and integration.
• Excellent communication skills, capable of conveying technical concepts clearly to both technical and non-technical stakeholders internationally.
• Ability and readiness to work in 24x7 rotational shifts to manage critical production incidents efficiently.