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.
Kuala Lumpur
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