Data Analyst II

Responsibilities

• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights.
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations.
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas.
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards.
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses.
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning.
• Contribute to the automation of recurring analyses and reporting workflows using Python.

Requirements

• 3+ years of experience in data analytics or a related role in a professional setting.
• 2+ years of experience working directly with Sales, Operations, Product, or equivalent business teams.
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets).
• Experience with Python for data analysis, automation, or scripting.
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar).
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights.
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Qualifications

• Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
• Familiarity with dbt for data modeling and transformation.
• Exposure to data pipeline orchestration tools (e.g., Airflow).
• Experience in fintech, financial services, or payments.
• Comfort operating in a fast-paced, high-growth environment with evolving priorities.

Skills

• Data visualization and storytelling skills.
• Ad-hoc analysis and deep dive investigations.
• Data tool development and process creation.
• Data collaboration and partnership.
• Data quality assurance and maintenance.
• Data automation and workflow contribution.
• Python programming.
• SQL for data manipulation and complex analysis.
• Business intelligence and data visualization tools proficiency.
• Generative AI and LLM-based tools familiarity.

Benefits

• Flexible work schedule with up to four weeks of fully remote work per year.
• Hybrid work environment combining office and remote work options.
• Competitive salary range of $93,600 - $117,000, with starting base pay dependent on factors including location, skills, experience, market demands, and internal pay parity.
• Equity and other forms of compensation may be provided as part of a total compensation package.

Pay

The expected salary range for this role is $93,600 - $117,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Schedule

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!