Data Analyst

The National Society of Leadership and Success (NSLS)

9d•Onsite

About The Position

The Data Analyst will join a growing data team and partner closely with our stakeholders to translate business questions into actionable insights. You'll embed yourself in marketing, finance, and sales to understand how the business operates, identify the right metrics and dimensions, and build visualizations that help stakeholders make faster, smarter decisions. A key early focus will be supporting our Redshift-to-Snowflake migration — auditing legacy dashboards, QA-ing reports, and validating data accuracy in the new environment.

Requirements

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

Responsibilities

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
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

Benefits

Standard business hours (9-5 or similar)
No on-call or off-hours expectations
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'
AI-assisted development: We actively encourage the use of AI tools to write better analyses faster and increase overall team velocity

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