Senior Data Analyst

• Analyze large, diverse datasets to identify trends, patterns, and insights that inform business decisions
• Develop structured analytical logic, methodologies, and frameworks that can be scaled and reused across multiple initiatives
• Build, refine, and maintain datasets that support analysis, reporting, modeling, or automation
• Collaborate with product, engineering, operations, and data teams to validate findings and ensure strategic alignment
• Produce clear, insightful summaries, visualizations, and recommendations for both technical and non-technical audiences
• Contribute to best practices in data quality, standardization, documentation, and analytical rigor
  

• Insight Impact - Demonstrated influence of your analyses on product, operational, or commercial decisions (e.g., decisions, roadmap changes, or process improvements driven by your work)
• Quality & Rigor - Consistently high-quality analyses with well-documented assumptions, logic, and reproducible methods
• Scalability of Work - Frameworks, queries, and logic that can be reused or extended across multiple initiatives, reducing ad hoc effort over time
• Stakeholder Satisfaction - Positive feedback from partner teams on clarity, reliability, and timeliness of your deliverables
• Data Quality Improvements - Measurable improvements in data accuracy, completeness, or consistency where your analysis informed changes (e.g., reduced defects, fewer manual corrections, more trusted reporting)
• Execution & Timeliness - Ability to manage multiple priorities and deliver on agreed timelines without sacrificing depth or quality
  

Requirements

• Proven experience as a Data Analyst or Senior Data Analyst working with complex, multi-source datasets
• Advanced proficiency in SQL and Python (or R) for data analysis and transformation
• Strong ability to identify patterns, relationships, and anomalies across large data environments
• Experience developing analytical frameworks, logic, or rules that support repeatable, scalable processes
• Excellent communication skills with the ability to translate technical findings into clear, actionable insights
• Experience in data quality, data management, analytics, or data operations is beneficial
• Familiarity with automation, metadata, or taxonomy work is a plus