GCP Tech vSME - Data Analytics

• Respond, diagnose, resolve, and track customer support queries across phone, email, and chat; ensure documentation is accurate and complete.
• Meet or exceed SLOs for response and resolution time; proactively manage queues to sustain performance.
• Maintain high CSAT and adhere to internal quality standards in ≥90% of audited cases.
• Assist L1/L2/Tiered teams: respond to consults from other technical support representatives using existing systems and tools; coach peers when needed.
• Establish root cause using approved troubleshooting tools and techniques; provide customer‑facing RCA that is clear, actionable, and timely.
• Assess business impact of issues; apply internal prioritization guidelines and justify priority for each customer report.
• Classify and tag incidents for retroactive analysis; document problem classes and preventative actions to improve product reliability and reduce repeat issues.
• File and collaborate on product bugs with Google engineers: reproduce issues, provide logs and steps, author or improve procedures and documentation, and suggest code‑level fixes where relevant.
• Community management activities as required (forums, posts, solutions articles, FAQs).
• Independently resolve escalations and complex technical incidents with transparent communication to internal/external stakeholders—aiming for no monitoring required by Google engineers.
• Handle architecture‑specific cases: provide solutions constrained to a particular product or defined subset of features.
• High‑touch assistance for top‑tier customers: develop deep understanding of their most pressing issues and advocate for them with engineering and program management.

Minimum Qualifications

• Language: Mandarin B2 (CEFR) or equivalent proficiency is a must; able to pass Versant benchmarks.
• English: professional working proficiency; confident written and verbal communication with global stakeholders.
• Technical Support Experience: Demonstrated success in L2/L3 support for cloud/data platforms, including incident ownership, RCA delivery, and cross‑functional collaboration.
• Troubleshooting & Analysis: Strong diagnostic skills (logs, metrics, tracing, performance analysis) and ability to translate findings into customer‑friendly RCA.
• 2-6 years of experience on google cloud or any cloud platform such as AWS or Azure

Preferred Skills & Product Certifications

Data Analytics — BigQuery Pod

• BigQuery
• Data Catalog
• Dataform
• Earth Engine

Dataflow & Pub/Sub Pod (SnL)

• Dataflow
• Pub/Sub
• Pub/Sub Lite
• Apache Flink for BigQuery
• Apache Kafka for BigQuery
• Dataprep

Telecom Subscriber Insights (Subgraph)

• Telecom data domain understanding; subscriber graph/subgraph concepts

Dataproc & Data Fusion Pod (SnL)

• Dataproc
• Dataproc Metastore
• Data Fusion
• Databricks
• Dataplex

Composer Pod (SnL)

• Cloud Composer (Airflow)

Certifications (nice‑to‑have):

• Google Cloud Professional Data Engineer, Professional Cloud Developer, Professional Cloud Architect (or relevant product certifications across the pods above).
• Related data engineering/streaming certifications (Apache Flink/Kafka), and vendor‑specific badges (Databricks, Airflow).

Working Conditions

• Standard business hours in MYT (GMT+8) with flexibility for on‑call rotations or priority escalations when required.
• Hybrid/onsite arrangements per program policy.