Senior Security Data Engineer
Listed on 2026-09-01
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IT/Tech
Cloud Computing: Infrastructure & Operations, Information Security & Data Protection, Cybersecurity
Obsidian Security is the leading SaaS security platform trusted by global enterprises like Snowflake T-Mobile and Algolia. We protect 200 organizations across North America Europe the Middle East Southeast Asia Australia and New Zealand including many of the worlds largest Fortune 1000 and Global 2000 companies.
Founded in 2017 and backed by top investors like Greylock Obsidian was built to close a critical gap: securing SaaS apps where business happens
Microsoft 365 Salesforce and hundreds more. The company does this by offering a complete SaaS security platform to reduce risk detect and respond to threats and prevent breaches at the source. Obsidian was built by leaders who redefined endpoint and identity security at Crowd Strike Okta Cylance and Carbon Black. Now theyre transforming how SaaS is secured.
With AI driving rapid SaaS growth and complexity agentic AI tools gain privileged access to sensitive data through integrations creating new risks most security tools miss. Obsidian uniquely detects anomalous OAuth token activity and manages integration risks. Major announcements are on the horizon. Recognizing that SaaS security needs to evolve Obsidian enables growing organizations to start with a lightweight prevention-focused browser extension and expand coverage over time.
With global momentum a growing partner ecosystem including Sentinel One Databricks and Google Cloud and a major fundraise ahead Obsidian is scaling rapidly toward long-term growth and IPO readiness.
About the Role
Were hiring Security Data Engineers to join our Manchester team and work at the heart of our SaaS and AI security platform. This is a data engineering role first youll spend most of your time building and maintaining the data pipelines that power Obsidians detection and analytics capabilities.
The role sits at an interesting intersection: the work is technically demanding data engineering but the context is security. You dont need a security CV you need to be a strong data engineer who is curious about how modern SaaS and AI platforms work and what makes them risky.
What youll do
- Build and maintain data retrieval integrations across major SaaS and AI platforms connecting to APIs handling auth flows and ensuring reliable telemetry ingestion.
- Design and develop dbt models in SQL on Clickhouse and Databricks transforming raw platform data into clean structured datasets ready for analysis.
- Build rule-based checks to identify risky configurations and unusual activity patterns across SaaS and AI platforms translating security insight into logic.
- Develop a working understanding of how SaaS and AI platforms are structured and where security risks emerge to inform what data we collect and what we look for.
- Debug data quality and detection issues in customer environments working closely with the wider engineering and customer success teams.
What were looking for
Requirements
- 4 years of hands-on data engineering experience including dbt and SQL.
- Strong SQL youre comfortable writing complex data models and transformations from scratch.
- Experience building or maintaining data pipelines that process high-volume event or log data.
- Comfortable working with REST APIs and integrating data from third-party platforms.
- Python proficiency for scripting data manipulation and pipeline logic.
- Some exposure to security concepts enough to understand what risky looks like in a SaaS or cloud context.
- This can come from working in a security company cloud engineering compliance or your own interest.
Nice to have
- Hands-on experience with Clickhouse or Databricks.
- Familiarity with SaaS platforms such as Google Workspace Microsoft 365 Salesforce or Okta from any angle (admin engineering or security).
- Understanding of identity and authentication concepts: OAuth SAML SSO and directory services.
- Experience working with security telemetry audit logs API event streams or similar.
- Interest in AI/LLM platforms and how they introduce new security considerations.
Why join us
- Work on a genuinely novel problem securing SaaS and AI platforms is one of the fastest-moving areas in enterprise security.
- Become a domain expert by learning from the industrys leading SaaS security…
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