Data Analyst, Abnormal Security

• 3+ years of experience working with large-scale data in analytical or product-oriented environments, with a strong focus on data exploration, interpretation, and communication
• Proficiency in writing complex SQL queries and building clean, reliable data models to support reporting and analysis
• Hands-on experience using DBT (Data Build Tool) to transform and organize data for downstream analytics workflows
• Strong grasp of data analyst best practices, including analysis reproducibility, validating results through testing and sanity checks, and communicating insights clearly to both technical and non-technical audiences
• Experience with at least one programming language (e.g., Python or R) for data exploration, statistical analysis, and automating reporting workflows; familiarity with DBT and/or Databricks is a plus
• Bachelor's degree in a quantitative field such as Data Science, Mathematics, Statistics, Computer Science, Information Systems, or a related discipline
• Demonstrated ability to translate ambiguous business questions into structured analyses and data models optimized for insight generation
• Strong track record of collaboration with cross-functional partners to deliver high-impact data solutions

Desirable

• Join our R&D Engine team as a Data Analyst, where you will build and maintain core data pipelines and dashboards supporting a broad range of R&D metrics, with a primary focus on infrastructure cost optimization, alongside areas such as AI enablement, engineering productivity, and other critical initiatives
• In this highly collaborative role, you'll work closely with engineers and finance leadership to define, track, and optimize the metrics that matter most for our organization's efficiency and innovation
• Bringing your expertise in SQL, dbt, and Python, you will ensure our team can deliver high-frequency reporting, provide ad hoc analyses, and enable rapid feedback loops for cost and operational effectiveness
• Your work will multiply our team's impact across all R&D initiatives
• Build, enhance, and maintain data pipelines and dashboards that drive transparency and optimization within our infrastructure cost program (across AWS, Azure, and related platforms)
• Support reporting and data development across AI enablement, engineering productivity, product usage, and other R&D-focused initiatives
• Partner with engineers and technical stakeholders to define, track, and optimize actionable metrics; participate in metric design, not just execution
• Apply strong SQL, dbt, and Python skills to automate measurement, ensure data quality, and maintain reliable operational metrics