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Data Modeling & Maintenance: Assist in maintaining scalable, well-documented dbt models that support regulatory reporting and platform safety monitoring.
Pipeline Optimization: Help build and optimize data pipelines in dbt, ensuring they meet the high standards of auditability required for compliance.
Cross-Functional Support: Collaborate with legal, policy, and engineering teams to help translate complex transparency requirements into technical data solutions.
Quality & Standards: Implement data definitions and documentation standards to improve data quality and support long-term maintainability of our safety metrics.
Technical Reviews: Participate in structured reviews of existing analytics infrastructure to identify performance improvements and alignment with reporting needs.
Self-Service Enablement: Support the development of our self-service ecosystem by contributing to intuitive semantic layers that serve a broad stakeholder base.
Monitoring: Help implement validation frameworks that enable performance tracking and early detection of data quality issues.
Foundational Experience: 0–2 years of experience in analytics engineering or data engineering, with a strong desire to work in regulated, safety, or compliance-oriented environments.
Technical Skills: Proficiency in SQL and Python, and familiarity with modern data stack tools (such as dbt, and control versioning)
Modeling Interest: A passion for learning how to architect clean, testable data models that support complex reporting needs.
Communication: Excellent communication skills, with the ability to learn how to translate technical details for legal and policy stakeholders.
Detail-Oriented: You are able to validate assumptions and prioritize accuracy in a high-stakes environment.
Mission-Driven: You have a passion for transparency, safety, and building data systems that serve social good.
Originally posted on Himalayas