Requirements:

• Experience building and operating production-grade data platforms, analytical data models, or large-scale data-processing applications.
• Strong SQL and dimensional or analytical data modelling experience.
• Strong Python software engineering experience.
• Demonstrated rigour around data correctness.
• Solid working understanding of infrastructure and observability concepts.
• Experience operating business-critical pipelines and diagnosing data, performance, and reliability issues in production.
• Familiarity with knowledge graphs, ontologies, and taxonomies.
• A strong bias towards automating repetitive work.
• Excellent problem-solving and communication skills.

Nice to Haves:

• A background in data science, statistics, or applied machine learning.
• Experience with SQL-based analytical platforms, dbt, object storage, and data catalogues.
• Experience with infrastructure inventory or CMDB data.
• Experience with metrics, logs, and vulnerability data.
• Experience with Superset or comparable BI and data-exploration tools.
• Experience with Linux, containers, and GitLab CI/CD.
• Experience with AWS services and cloud SDKs.

What You'll Be Doing:

• Design and build data models for infrastructure and operational data.
• Integrate inventory, configuration, security, and observability data from multiple systems.
• Keep key counts and metrics consistent across different consumers.
• Automate data processing, validation, and delivery.
• Investigate and resolve data-quality, freshness, and performance issues.
• Collaborate closely with infrastructure, security, engineering, and observability teams.
• Take ownership of systems end-to-end.

Perks and Benefits:

• Equal opportunity employer with a focus on diversity.
• Empower employees to work openly and respectfully.
• Offering initiatives and programs to enable employees to achieve a healthy work-life balance.