Lead Data Analyst

Role Overview

The Lead Data Analyst is a senior individual contributor who drives data-informed decision-making across the organization. You will lead complex analytics end-to-end, mentor junior analysts, and partner with business stakeholders to deliver insights that shape strategy and operations.

Responsibilities

• Lead end-to-end analytical projects: scoping, data collection, modeling, and executive-ready presentations.
• Serve as the primary analytics point of contact for business domains (e.g., marketing, product, finance, operations).
• Define and maintain KPIs, dashboards, and reporting frameworks aligned to organizational objectives.
• Turn ambiguous business questions into structured analytical problems with clear deliverables.
• Execute advanced analytics, including:
  • statistical modeling and forecasting
  • cohort analysis
  • segmentation
  • A/B testing
• Build and maintain complex SQL queries, data pipelines, and analytical datasets in cloud data warehouse environments.
• Develop predictive models and apply machine learning where appropriate.
• Ensure data quality, integrity, and consistency across outputs.
• Create executive-level dashboards and self-service reporting using BI tools such as Tableau, Power BI, and Looker.
• Present insights to technical and non-technical audiences, influencing decisions at all levels.
• Document methodologies, data definitions, and business logic.
• Mentor and coach junior/mid-level analysts, including conducting code reviews and providing technical guidance.
• Partner cross-functionally with Data Engineering, Product, Finance, and Marketing on data strategy and priorities.
• Contribute to team best practices (coding standards, peer review, analytical documentation).
• Travel up to 15% annually (domestic and international).

Requirements

• 5+ years of experience in a data analyst/BI/analytical role with a Bachelor’s in a quantitative field, or 3+ years with a Master’s (or equivalent combination).
• Advanced SQL and experience with large-scale cloud data warehouses such as Snowflake, BigQuery, Redshift, or similar.
• Hands-on experience with BI/visualization tools: Tableau, Power BI, Looker, or equivalent.
• Strong working knowledge of Python or R for data manipulation, statistical analysis, and automation.
• Understanding of Azure (as stated in the posting).

Nice to Have

• Experience applying machine learning techniques for business value (implied by requirements).
• Experience with A/B testing and advanced statistical/experimental analysis.