Data Engineer

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 world’s 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 CrowdStrike, Okta, Cylance, and Carbon Black. Now, they’re 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 SentinelOne, Databricks, and Google Cloud, and a major fundraise ahead, Obsidian is scaling rapidly toward long-term growth and IPO readiness. About the Role As a Data Engineer at Obsidian, you'll: Own and evolve the data pipelines behind one of Obsidian's core products Build and maintain data transformations and orchestrated jobs that turn raw signal into attributed, enriched data at scale Keep customer analytics datasets accurate, fresh, and reliable across multiple data stores Extend and improve our data attribution engine, including its rule-based and LLM-assisted curation stages Make occasional changes to the Go service that exposes this data through our APIs, working alongside backend engineers Collaborate with product managers, backend engineers, and the teams who turn this data into customer-facing functionality Champion data correctness, observability, and clean, testable transformations Participate in code reviews and technical discussions to continuously raise engineering standards What's in it for you Own the data foundations of a core product used by enterprises worldwide Work alongside a talented, supportive team in a collaborative culture Grow your skills across modern data tooling, streaming systems, and LLM-assisted workflows Gain exposure to a cloud-agnostic platform spanning AWS and GCP Be part of an innovative, growing company where your work makes a real impact Enjoy hybrid working, with supported remote working and great office spaces in Cheltenham and Manchester Required Skills and Experience: 3–6 years of experience in a data engineering or software engineering role Strong SQL and hands-on experience building production data pipelines Experience with a modern data orchestrator such as Dagster, Airflow, or similar Proficiency with a data transformation framework such as dbt Proficiency in Python Familiarity with Git and CI/CD tooling such as GitLab CI/CD Familiarity with relational databases (e.g., Postgres) and cloud data warehouses A bias toward data quality, testing, and maintainable, well-documented work Experience collaborating in a team environment and adapting to changing requirements Desirable Experience Experience with Databricks/Spark or other large-scale analytics platforms Exposure to event/streaming systems such as Kafka Existing Go experience for occasional API changes Familiarity with containerization and orchestration (Docker, Kubernetes) Exposure to LLM-assisted data workflows Experience with cloud platforms (AWS or GCP) and object storage (S3/GCS) Exposure to observability tooling such as Grafana or Prometheus