Data Analyst

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Description

Key Responsibilities Insight Generation & Business Strategy: Partner with cross-functional leadership (Product, Growth, Finance, Operations) to identify trends, diagnose churn/growth drivers, and discover high-value business opportunities. Analytics Engineering & Data Modeling: Write clean, modular, and version-controlled SQL models (using tools like dbt) to transform raw data into well-structured, production-ready tables. Modern Visualization & Storytelling: Design intuitive, dynamic dashboards and narrative reports (using Lightdash, Looker, Metabase, Tableau, or Power BI) that drive decision-making rather than just display metrics. Data Quality & Governance: Establish data definitions, document metrics in a central data catalog, and ensure high standards for data accuracy, testing, and reliability. AI & Workflow Automation: Leverage AI-assisted analytics workflows and automated pipelines to speed up data exploration and deliver real-time operational alerts. Requirements & Qualifications Experience: 2–5 years of experience in a data analytics, product analytics, or business intelligence role. Advanced SQL & Modeling: Strong mastery of SQL (window functions, CTEs, performance optimization) and familiarity with modern data transformation practices. Modern Data Stack: Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery, Databricks) and BI/semantic layer tools. Business Acumen & Storytelling: Ability to translate complex quantitative findings into clear, ac

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