Data Analyst

About the role

The Data Analyst will join a team of 80+ purpose-driven staff members in a friendly, focused, fast-paced entrepreneurial environment. The National Society of Leadership and Success (NSLS) is the largest accredited leadership honor society in the United States, with over 800 chapters and more than 2 million members.

Responsibilities

• In Your First 6 Months
• Support the Snowflake migration: Audit and QA legacy Redshift dashboards and reports, validate logic against new dbt models, and help ensure a clean cutover
• Build business-facing dashboards: Develop intuitive, self-service reports in Hex that give marketing, finance, and sales teams the visibility they need
• Establish metric definitions: Partner with stakeholders to translate business language into well-defined metrics and dimensions, then document them for shared understanding
• Collaborate with the data team: Work in a sprint-based workflow with our Data Engineer, Analytics Engineer, BI & Automation Lead, and Head of Data
• Ongoing Responsibilities
• Write and maintain SQL and dbt models: Develop clean, well-documented transformations that power gold-layer business reporting
• Embed with business teams: Proactively identify the questions being asked by marketing, finance, and sales — and bring data products to them before they have to ask
• Democratize data access: Build dashboards and self-service tooling that reduce ad hoc requests and empower stakeholders to find answers independently
• Tell stories through data: Communicate findings in a way that is clear, compelling, and actionable for both technical and non-technical audiences
• Run analyses and experiments: Design and interpret A/B tests, build forecasting models, and apply statistical methods (regression, cohort analysis, confidence intervals) to support business decisions
• Use AI to work smarter: Leverage AI tools (Claude, Copilot, Cursor, or similar) to accelerate analysis, automate repetitive tasks, and expand what's possible

Qualifications

• 2–3 years of experience as a Data Analyst, Analytics Engineer, or similar role
• Strong SQL skills: You write clean, advanced SQL including CTEs, window functions, and optimized queries that others can read and maintain
• dbt proficiency: You've worked with dbt in a production environment and understand modeling best practices
• Visualization experience: You've built dashboards and reports in Hex, Looker, Tableau, or a comparable BI tool — and you know how to design for clarity, not just completeness
• Stakeholder communication: You can bridge the gap between technical and non-technical audiences, explain your methodology, and present findings with confidence
• Statistical fundamentals: You understand hypothesis testing, A/B test design, regression analysis, and confidence intervals, and can apply them correctly
• Forecasting experience: You've built or contributed to forecasting models using cohort trends, maturity curves, or regression techniques
• AI-assisted development: Proficient with AI tools to accelerate work, debug queries, and learn new technologies quickly

Nice To Haves

• Experience with Snowflake as a data warehouse
• Python fundamentals (pandas, notebooks) for data wrangling or analysis
• Background in marketing, finance, or sales analytics
• Familiarity with HubSpot or similar CRM data

Who You Are

• A storyteller: You don't just pull numbers, you craft narratives that make data actionable for the people who need it
• Proactively curious: You surface questions stakeholders should be asking and bring answers before they're requested
• A bridge-builder: You're equally comfortable whiteboarding with a VP as you are writing a dbt model, and you translate between both worlds fluently
• Quality-focused: You document your work, write readable SQL, and leave the codebase better than you found it
• AI-native: You use AI tools as a genuine force multiplier while maintaining rigor and ownership over your output
• Mission-driven: You want your work to matter: to students, to the organization, and beyond a dashboard

How We Work

• Sprint-based workflow: Bi-weekly sprints with planning, standups twice per week, and regular retrospectives
• Weekly 1:1s: Regular check-ins with the Head of Data for feedback, support, and career growth
• Collaborative code review: Your SQL and dbt models will be reviewed and you'll review others'
• Work-life balance: Standard business hours (9-5 or similar), no on-call or off-hours expectations
• AI-assisted development: We actively encourage the use of AI tools to write better analyses faster and increase overall team velocity

Tech Stack

• Data Warehouse: Snowflake (migrating from Redshift)
• Transformation: dbt Cloud
• Visualization: Hex
• Customer Data Platform: PostHog
• Infrastructure: AWS
• Source Systems: HubSpot, Drupal, Symfony, Shopify (100+ tables,

Benefits

The National Society of Leadership and Success is an equal opportunity employer committed to diversity, equality, and inclusion

Pay

Details TBD

Schedule

Standard business hours (9-5 or similar)