Senior Data Analyst

As a Senior Data Analyst, you will be the bridge between raw data and strategic execution. We are looking for a technical powerhouse who lives and breathes SQL . You won't just be running queries; you will be designing complex data models, optimizing performance for massive datasets, and mentoring junior analysts. Your insights will directly influence our product roadmap and business strategy.

Key Responsibilities

• Advanced SQL Development: Write, troubleshoot, and optimize complex SQL queries involving multi-table joins, subqueries, and window functions to extract insights from relational databases.
• Data Modeling & Architecture: Design and maintain robust data models and schemas that ensure data integrity and high performance for BI tools.
• Stakeholder Partnership: Act as a strategic partner to Product, Marketing, and Finance teams, translating ambiguous business questions into structured analytical projects.
• Dashboarding & Visualization: Build and automate high-impact dashboards (Tableau, Power BI, or Looker) that track KPIs and provide real-time visibility into business health.
• Performance Tuning: Monitor and optimize query performance, identifying bottlenecks and implementing indexing or partitioning strategies to handle scale.
• Mentorship: Lead code reviews for SQL and data logic, providing guidance to junior analysts to ensure high standards of data accuracy and efficiency.
• ETL Collaboration: Partner with Data Engineers to streamline data pipelines and ensure the "source of truth" is reliable and well-documented.

Required Qualifications

• Experience: 5+ years of professional experience in data analytics, business intelligence, or a related quantitative field.
• SQL Mastery: Expert-level SQL skills are mandatory (PostgreSQL, Snowflake, BigQuery, or SQL Server). You should be comfortable with CTEs, window functions, and complex query optimization.
• BI Tools: Extensive experience building scalable reporting solutions in tools like Tableau, Power BI, Looker, or Sigma .
• Statistical Foundation: Strong understanding of statistical concepts (A/B testing, regression, correlation vs. causation).
• Analytical Rigor: Ability to clean and validate "messy" data, ensuring that insights are based on high-quality, verified sources.
• Communication: Proven ability to present complex technical findings to non-technical executives in a clear, actionable story.

Preferred Skills (The "Plus" List)

• Experience with Python or R for advanced statistical modeling or automation.
• Familiarity with modern data stack tools like dbt (data build tool) .
• Knowledge of cloud data warehouses (e.g., Snowflake, AWS Redshift, Google BigQuery).
• Background in a specific industry (e.g., SaaS, FinTech, or E-commerce).