Data Analyst

About the Role

This position is responsible for underpinning the analytical aspects of both the product and business operations by converting intricate datasets into practical insights, dynamic dashboards, and predictive analytics models.

The role involves collaboration with product managers, data engineers, and company leadership to enable decisions that are thoroughly grounded in data across essential business KPIs.

Key Responsibilities

• Create, develop, and sustain robust SQL-based data frameworks, dimensional data structures, and automated dashboard reporting using platforms such as Looker or Tableau.
• Work closely with product and engineering units to establish key performance indicators, monitor feature usage, and evaluate the effects of new product launches.
• Conduct comprehensive exploratory analyses to uncover patterns in user behavior, identify obstacles to retention, and discover potential areas for expansion.
• Develop and maintain ETL workflows using Python and SQL to assure precise and dependable data flow within the data warehouse.
• Design experiments with A/B testing protocols, compute statistical validity, and provide actionable experiment insights.
• Summarize and communicate in-depth technical results into succinct reports tailored for executives to influence strategic initiatives.

Candidate Requirements

• Between three and six years of professional experience in data analytics, business intelligence, or analytics engineering within technology-focused organizations.
• Proficient with advanced SQL techniques including window functions, common table expressions (CTEs), performance optimization, and in-depth knowledge of data warehouse platforms such as Snowflake or BigQuery.
• Experienced in Python programming, particularly libraries like Pandas and NumPy, and adept at using data visualization software such as Looker, Tableau, or Mode.
• Good grasp of statistical methodologies, hypothesis testing, and experimental designs relevant to product analytics.
• Educational background with a bachelor's degree in Statistics, Computer Science, Economics, Mathematics, or similar quantitative disciplines.
• Desirable additional skills include familiarity with dbt for data transformation and introductory knowledge of machine learning regression techniques.