Data Analytics SME

Job Description:

5 to 7 Years of experience in Looker Studio,Original,Pro, Looker Cloud..

Act as go-expert for customer issues, provide RCAworkarounds and best practices to customers and internal teams.

Own and resolve complex issues for Google Cloud Data Analytics products like BigQuery,Storage, Airflow Composer, Dataflow, Pub/Sub.

Deep dive into logs, query plans, job graphs and pipeline failures, toidentify root causes.

Strong expertise in Troubleshoot data pipeline failures, latency issues, quota errors, Monitor system health and job failures.

Exposure in configuring and managing network devices and services

Own incidents end-to-end: triage, root cause analysis, resolution, and communication with stakeholders.

Strong knowledge in IAM, VPC, storage, quotas, and GCP project setup. Experience with Python, SQL, and Shell scripting for troubleshooting. Familiarity with CI/CD, Git, and Infrastructure as Code. Strong analytical and problem-solving skills for production issues. Excellent communication skills to explain technical issues to both technical and non-technical stakeholders.

Use Cloud Logging, Cloud Monitoring to collect logs, metrics and traces of debugging. Reproduce the customer issues in the test environment and validate fixes before roll out.

Advanced knowledge of BigQuery performance tuning including materialized views, partitioning strategies, and clustering to optimize high-volume queries.

In-depth experience with Apache Beam programming model for complex Dataflow transformations, including stateful processing and side inputs.

Ability to design and implement highly available and scalable data architectures in GCP, including cross-region disaster recovery and failover strategies.

Proficiency in advanced Airflow concepts, such as custom operators, dynamic DAG generation, and implementing robust error handling and alerting frameworks.

Expert-level debugging of distributed systems, utilizing advanced tracing (Cloud Trace) and profiling techniques to identify bottlenecks in complex data pipelines.

Key Responsibilities*

Diagnosing root causes and resolving technical issues across hardware, software, and networking systems.

Delivering technical support to internal and external users via multiple communication channels.

Provisioning and deprovisioning cloud infrastructure, including compute, storage, and networking components, as required.

Articulating technical concepts clearly and effectively to stakeholders and end users