Wei Zhang Senior Post-Sales Engineer
New York, NY • post.sales.eng@gmail.com • +1 212-4471
Profile Summary
- Senior Post-Sales Engineer with 7 years of experience across Mid-Market and Enterprise data platform accounts serving application developers, data engineers, and platform leads, specializing in technical implementation, integration delivery, and lifecycle ownership.
- Hands-on across core platform (MongoDB Atlas), primary cloud (AWS), scripting language (Node.js), integration surface (Atlas API and drivers), observability tool (MongoDB Atlas metrics and Datadog), deployment shape (dedicated Atlas clusters with PrivateLink), and a product cert (MongoDB Associate Developer), with strong fundamentals in hands-on engineering, deep product knowledge, and lifecycle ownership from POC to renewal.
- Deep expertise in lifecycle technical ownership, implementation to first production use, integration delivery, and technical wins that anchor renewal, using methodologies such as staged implementation playbooks and post-POC technical handover from the AE to ship customers that go live on what they actually bought.
- Pairs tightly with Sales Engineers, Account Executives, Engineering, Product, and Customer Success inside hybrid SE pods with quarterly on-site implementation weeks, showing up to deal-strategy syncs, cutover bridges, and roadmap reviews with a pragmatic, ship-the-deployment mindset.
- Senior Post-Sales Engineer who shares implementation craft and fosters a culture of implementations that survive their first peak event and reference architectures the customer can keep running through post-launch readouts and design clinics, while running implementation review guild and post-launch readouts and authoring widely shared playbooks and reference integrations.
Tools & Skills
- Languages & Scripting:
- Node.js, Python, Java, Go, TypeScript, Bash, SQL, MQL, YAML, JSON
- Platform & Product:
- MongoDB Atlas, Atlas Search, Atlas Vector Search, Atlas Stream Processing, Realm, Charts, Compass
- Cloud, Infra & Deployment:
- AWS, GCP, Azure, Kubernetes, Helm, Docker, Terraform, PrivateLink, VPC peering
- Integration & APIs:
- Atlas API, MongoDB drivers, Kafka Connect, Change Streams, Atlas Data API, webhooks, OAuth, SCIM, SAML SSO
- Troubleshooting & Observability:
- Atlas metrics, Datadog, Grafana, Prometheus, mongotop, mongostat, explain plans, slow-query analysis, kubectl
- Implementation & Delivery:
- staged go-live plans, schema design reviews, index reviews, data modeling workshops, runbook authoring, cutover runs
- Support & Escalation:
- Jira, Zendesk, PagerDuty, P1 and P2 escalation handling, joint debugging with Core Server, RCA writing
- Certifications:
- MongoDB Associate Developer, MongoDB Associate DBA, AWS Solutions Architect Associate, HashiCorp Terraform Associate
Education
New York University, Courant Institute
M.S. in Computer Science
Work Experience
MongoDB
Senior Post-Sales Engineer
- Own the technical handover from the AE and SE at deal close, taking 22 Mid-Market and Enterprise Atlas customers through a staged go-live plan that covers PrivateLink setup, replica-set topology, driver wiring, and first production write, landing time-to-production at 42 days from contract signature.
- Sit as the trusted technical advisor on Atlas through data modeling and index reviews with the customer's application developers and data engineers, recommending document shapes, sharding keys, and aggregation patterns against their real workloads, and delivering 54 tailored workshops across the book.
- Build customer integrations on the Atlas API, drivers, and Kafka Connect surface, writing sample Node.js and Python against the customer's services, reviewing connection pooling and Change Streams setups, and shipping 31 integrations to production with a median build time of under 5 days per integration.
- Design the deployment to fit the customer's real workflow, working through schema design and aggregation pipelines against their business model, and shipping 18 tailored workloads on event ingestion and vector search, each closed out with a reference repo and data model doc handed back to the customer's team.
- Take the non-trivial tickets that bounce off the first-line queue, owning performance and replication issues end-to-end through explain-plan reads and oplog inspection, repro clusters, and joint debugging with Core Server, closing 47 tickets across the book at a median time to resolution of under 18 hours.
- Watch Atlas telemetry and slow-query patterns across the book on a monthly cluster reviews cadence, spotting under-tuned clusters and missing indexes before the customer notices, shipping 29 proactive optimizations that cut customer cluster spend by 23% while holding latency flat.
- Partner with Sales Engineers and Account Executives on renewal and expansion conversations, with technical expansion architectures anchoring each motion (Atlas Search, Vector Search, Stream Processing), and anchoring $8.4M of expansion pipeline across the year through architectures the customer trusted enough to sign.
Cloudera
Sales Engineer
- Trained customer engineers on Cloudera Data Platform through hands-on workshops and tailored runbooks, pairing with internal champions on the customer side, taking 210 engineers through enablement and contributing 14 KB articles back to the internal knowledge base.
- Closed the field-to-product loop through monthly product council with Product and Engineering, aggregating deployment friction, missing connectors, and recurring gaps from real implementations, filing 22 structured feature gaps that drove 7 roadmap items into the year's release.
- Coordinated major launches through cross-team launch bridges with Engineering, Support, and the customer's on-call, owning 16 production cutovers to clean handover at a median cutover window of under 3 hours, with public-facing post-launch readouts inside 48 hours.
- Worked tightly with Sales, Engineering, Product, Support, and Customer Success to drive POC-to-production handovers and joint root-cause analysis, strategic-account steering, and peak-event readiness, authoring 8 implementation playbooks that became the team's onboarding standard and mentoring 4 incoming engineers through their first implementations.