Scaled Customer Success Manager
T
Tiger DataPostgreSQL platform
US Full-time, Eastern or Central time zonesFull-TimeMiddle
Salary90000 - 140000 USD per year
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Job Details
- Experience
- 2+ years
- Required Skills
- AWSPostgreSQLSQLSalesforceHubSpot
Requirements
- 2+ years of experience as a Customer Success Manager (or similar post-sales role) in a scaling B2B SaaS organization
- Experience working with technical products
- Familiarity with databases (Postgres/SQL), AWS, or infrastructure concepts is strongly preferred
- Can confidently engage technical stakeholders (DevOps engineers, data engineers, engineering leaders) and translate between technical complexity and business value
- Experience running segmented or scaled customer engagement programs (1:many campaigns, webinars, digital outreach)
- Comfortable analyzing product usage data to identify churn risk and expansion opportunities
- Have partnered closely with RevOps and Marketing on lifecycle campaigns or segmentation efforts
- Have a working opinion on how AI is reshaping Customer Success and actively use tools like ChatGPT, Claude, or Gemini to improve efficiency and quality
- Curious, decisive, and proactive — you think in systems and solve for scale
- Strong written and verbal communication skills and can drive clarity in async environments
- Thrive in fast-paced environments where autonomy and collaboration go hand in hand
Responsibilities
- Owning the health and outcomes of our scaled portfolio — including onboarding acceleration, adoption growth, retention risk mitigation, and expansion signal qualification across ~1,500 customers
- Designing and executing segmented 1:many engagement campaigns using tools like HubSpot, Salesforce, and Outreach
- Building personalized monthly adoption email campaigns that improve engagement, clarify customer use cases, and increase adoption of sticky features
- Launching and running a repeatable monthly webinar cadence (product roadmap sessions, customer roundtables, and best-practice sharing)
- Designing and running structured, time-bound plays focused on re-engaging dormant accounts, mitigating churn risk, and identifying and qualifying expansion opportunities
- Analyzing product usage data and telemetry to identify leading indicators of retention risk and growth opportunity
- Generating and qualifying expansion leads (CSQLs) through usage insights and structured discovery — maintaining a strong close rate in partnership with Sales
- Collaborating cross-functionally with RevOps and Marketing to refine segmentation, health scoring, and lifecycle campaign infrastructure
- Leveraging AI tools like Claude, ChatGPT, and Gemini to draft campaigns, surface risk patterns, summarize usage insights, and improve CS leverage
- Providing structured feedback to Product and Engineering based on scaled customer insights
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