Analytics Engineer, Safety Systems

Responsibilities

• Design and maintain canonical datasets that serve as sources of truth for safety metrics.
• Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently.
• Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making needs and design intuitive ways to consume complex safety metrics, including dashboards, reports, agentic workflows and other data products.
• Ensure that analytics and visualizations are both accurate and user-friendly, incorporating user experience principles.
• Advocate for data quality, consistency, and reliability across analytics products.

Requirements

• 5+ years of experience in a relevant data role within dynamic, outcome-driven organizations.
• Demonstrated ability to independently own ambiguous, high-impact business problems, from structuring the analytical approach to driving clear recommendations and execution.
• Highly autonomous and resourceful, with a track record of navigating data, stakeholder, and operational blockers.
• Highly skilled in SQL, with extensive experience extracting large datasets and designing ETL workflows.
• Experienced in using business intelligence tools, such as Tableau and Looker, to communicate insights and enable self-serve.
• Excellent communication skills, with demonstrated ability to collaborate with researchers, engineers, data scientists, and executives alike.
• Best-in-class attention to detail and unwavering commitment to accuracy.
• Proven track record of delivering significant business impact, preferably within Finance, Sales, Support, or other GTM domains.

Nice-to-Haves

• Experience using or building agentic data tools, LLM-powered analytics, or other AI-assisted data workflows.
• Experience in trust and safety, integrity, anti-abuse, or related fields.
• Familiarity with advanced custom visualizations, such as Streamlit and Plotly Dash.
• Demonstrated prior experience in NLP, large language models, or generative AI.
• Experience building data products used by a broad range of stakeholders, from technical practitioners to company leadership.