Customer Success Operations Analyst

Obsidian-Security; Dallas (TX); On-site; USD 110,000 - 165,000; Full time

Job summary

Obsidian Security is building a new Service Operations function within Customer Success to modernize how we structure, access, and act on customer data. You will own the reporting and automation layer, turning CS data into automated reporting and AI-assisted tools that enable health tracking and executive dashboards.

You’ll shape deterministic and AI/LLM-driven workflows, replace handoffs with automated processes, and collaborate across teams to ensure secure, auditable data access and high data

Qualifications

• AI-first is the preferred approach to automate reporting.
• Proficiency with Databricks for data modeling and governance.
• Python or similar scripting language for data transformation.

Responsibilities

• Own the reporting and automation layer for Customer Success data.
• Design AI-first workflows to surface customer health insights and dashboards.
• Automate recurring CS workflows beyond reporting (renewal tracking, ticket triage).
• Help define secure, auditable data access for CS activities in partnership with Security.
• Maintain data quality and documentation for CS data sources.
• Collaborate with Business Systems, Product/Engineering, and CS teams to shape data flows.

Skills

AI-first mindset

Databricks

Python

Salesforce data

Strong communication

Tools

Zendesk

Salesforce

Slack

Data warehouse

Job description

Obsidian Security is a global leader in cyber security protecting the SaaS and non-human identity layer modern enterprises run on — from Salesforce and Snowflake to the AI agents now deployed inside them. The Obsidian Security platform gives unified visibility into every human and machine identity, app, and integration across their SaaS estate, detects identity-based and supply chain attacks in real time, and enforces least-privilege access before it's exploited. Trusted by major Fortune 500 companies T-Mobile, Workday, Snowflake, and S&P Global, Obsidian ranked No. 95 on the 2025 Deloitte Technology Fast 500™, growing nearly 1000% from 2021–2024 — helping CISOs turn an unmonitored attack surface into one they can govern with confidence. Obsidian has also been recognized by Forbes as America's Best Startup Employers in 2026.

In August 2026, Obsidian raised $85 million in Series D financing led by Crescent Cove Advisors, with participation from existing investors including Greylock Partners, Menlo Ventures, Norwest Venture Partners, IVP, Wing Ventures, and GV — pushing Obsidian's valuation to $1.1 billion, crossing into unicorn status. Obsidian is using the funding to deepen its R&D in agentic AI security and extend its platform as the standard for governing what AI agents can access and do inside third-party applications.

With global momentum, a growing partner ecosystem including SentinelOne, Databricks, and Google Cloud, and fresh capital from its Series D behind it, Obsidian is scaling rapidly toward long-term growth and IPO readiness.

About the Team

We’re building a new Service Operations function within Customer Success to modernize how we structure, access, and act on customer data. This is a foundational role: you’ll be the primary consumer of the data built and owned by Business Systems, transforming it into automated reporting and AI-assisted tools that enable customer health tracking, streamline QBRs and EBRs, and provide executives with clear visibility into customer outcomes.

About the Role

• Own the reporting and automation layer for Customer Success — translate stakeholder needs for account health, QBR/EBR decks, and executive dashboards into field-level requirements, then build the reporting and automation on top of the Customer Success data mart.
• Default to AI-first workflows — shape the roadmap for both deterministic (data plumbing) and non-deterministic (AI/LLM-driven) automation that surfaces customer insights, health checks, and recurring reports, replacing manual, ad hoc work wherever possible.
• Automate recurring Customer Success workflows beyond reporting, including renewal/adoption tracking, repetitive support tasks like ticket triage and diagnostics, and cross-platform automation that connects support tools (e.g., Zendesk) with systems like Salesforce, Slack, and the data warehouse to cut down manual handoffs.
• Help define a secure, auditable data access model for Customer Success workflows, in partnership with Business Systems and Security (who own implementation).
• Maintain data quality and documentation for Customer Success data sources, flagging gaps, inconsistencies, or governance issues as you find them.
• Partner across Business Systems, Product/Engineering, and Customer Success (TAM and Support) to shape how data flows into the reports and tools people use every day.

About You

• An AI-first approach to problem-solving — you default to evaluating where agentic or LLM-driven workflows can replace manual, ad hoc reporting rather than reaching for another one-off script or dashboard.
• Hands-on experience with Databricks (or a comparable modern data platform), including querying, data modeling on governed marts, and metric/semantic views.
• Familiarity with Python or another scripting language for data transformation and automation.
• Strong communication skills — able to translate ambiguous business reporting needs into concrete data requirements.
• Experience with Salesforce data and/or customer success platforms (e.g., Totango,