The National Society of Leadership and Success (NSLS)

Data Analyst

• 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

Data Engineer

• Contribute to the Snowflake migration: Work with the broader data team to deprecate our legacy Redshift and Apache Hop infrastructure by completing the migration to Snowflake and dbt Cloud
• Build production-grade dbt pipelines: Develop and maintain SQL transformations in dbt that power analytics for business stakeholders across the organization
• Establish data architecture: Refine and maintain our medallion architecture (bronze, silver, and gold layers) to create clear separation of concerns and a single source of truth
• Collaborate with the data team: Partner with our AWS Engineer, Analytics Engineer, and Business Analyst in a sprint-based workflow with code reviews and regular standups
• Maintain dbt transformations (60-70% of role): Own approximately 15-20 core models and summary views that drive business reporting, ensuring they're performant, well-documented, and easy to maintain
• Build new data pipelines: Ingest data from APIs and new sources as business needs evolve
• Enable reverse ETL: Develop and manage batch processes to send transformed data to downstream services like HubSpot using tools like Hightouch
• Monitor data quality: Implement testing and alerting to catch issues before they impact stakeholders
• Contribute to technical standards: Help establish and maintain best practices for code quality, documentation, and data modeling

Full-stack Engineer

• Design and build modular, flexible architecture to support rapid experimentation and user journey testing.
• Develop and optimize engagement-driven features (e.g., smart onboarding, progress celebrations, contextual nudges).
• Integrate lifecycle communication systems (in-app, push, SMS/email) in partnership with marketing.
• Leverage analytics (PostHog or similar) to identify friction points and inform product iteration.
• Collaborate with AI engineers to embed LLM-driven experiences into the platform.
• Partner with cross-functional teams to prioritize and ship improvements that drive user engagement.
• Establish and share best practices for turning features into habit-forming experiences.

Data Analyst

Data Engineer

Senior Product Engineer – AI Engagement