Data Lead

About the role

In this Data Lead position at Stepful, you will own the end-to-end data strategy that powers our workforce platform training healthcare workers and connecting them with major health systems. You will manage our data infrastructure, analytics, and insights while maintaining a hands-on approach to coding and modeling to ensure decisions are grounded in robust evidence. You will define and track key metrics regarding student journeys and overall business performance, translating complex findings into clear narratives for diverse audiences. You will create dashboards and self-serve tools for internal teams, enabling product, growth, and operations to move with speed and confidence. You will collaborate closely with Product and Growth teams on A/B testing and experimentation, designing analyses that clarify impact and guide iterative improvements. You will perform deep-dive investigations to influence company strategy and budget decisions, ensuring resources are allocated to the highest-return opportunities. You will write production-grade SQL and Python code, building reliable pipelines that support our scaling needs and maintain rigorous standards for accuracy. You will implement scalable data governance and quality standards, fostering a culture where data integrity is foundational and actionable across the organization.

Key facts

What you'll do

• Manage and mentor a team of three data analysts and engineers, providing guidance, feedback, and career development to elevate individual and team performance.
• Oversee the entire data platform, including pipelines, warehousing, transformation, and BI tools, ensuring reliability, scalability, and alignment with business needs.
• Define and track key metrics regarding student journeys and overall business performance, establishing a clear framework for measurement and continuous improvement.
• Create dashboards and self-serve tools for internal teams, enabling stakeholders to explore data, answer their own questions, and drive data-informed decisions.
• Collaborate with Product and Growth teams on A/B testing and experimentation, from hypothesis formulation through analysis and implementation of learnings.
• Perform deep-dive analyses to influence company strategy and budget decisions, synthesizing complex information into actionable recommendations.
• Write production-grade SQL and Python code, emphasizing maintainability, performance, and robustness in a production environment.
• Implement scalable data governance and quality standards, putting processes in place that prevent issues and enable trust in data across the organization.
• Partner with cross-functional stakeholders to translate ambiguous problems into structured analytical approaches and clearly defined success metrics.
• Design experiments and interpret results in fast-growing companies, balancing rigor with the need for speed in a startup context.
• Communicate findings effectively to non-technical stakeholders, using storytelling and visualization to make data accessible and impactful.
• Evaluate new tools and methodologies to modernize the stack, improving efficiency and insight generation across data workflows.
• Support the development of data literacy across the organization by enabling teams to understand and use data confidently and correctly.
• Ensure that data practices support compliance, security, and operational best practices while remaining aligned with company goals and user needs.

Requirements

• 7+ years of professional experience in data engineering and analytics, with a track record of delivering impactful projects in a fast-paced environment.
• 2+ years of experience in a management or leadership role, demonstrating the ability to guide, motivate, and develop a technical team.
• Proficiency in SQL and Python, with the ability to write efficient, well-structured code that scales and is easy to maintain.
• Experience with modern data stack tools such as dbt, Snowflake, BigQuery, Airflow, Looker, or Metabase, showing familiarity with how these tools integrate into a cohesive system.
• Ability to connect technical data work to business outcomes, translating analysis into insights that drive measurable impact on the organization.
• Experience designing and interpreting experiments in fast-growing companies, understanding the nuances of causal inference in dynamic environments.
• Strong communication skills for presenting findings to non-technical stakeholders, with the ability to simplify complexity without losing nuance.
• A collaborative mindset, working effectively with product, engineering, operations, and executive teams to align on priorities and solve problems.
• Comfort working in an ambiguous, fast-moving startup environment, making decisions with incomplete information and iterating based on new evidence.
• Ownership of end-to-end analytical workflows, from data requirements and collection through modeling, validation, and insight delivery.
• Commitment to maintaining high standards for data quality, documentation, and reproducibility across all analytical processes.
• Willingness to contribute hands-on where needed, balancing strategic oversight with tactical execution to keep the team moving efficiently.

Nice to have

• Experience scaling a data function at an early or growth-stage startup, navigating the challenges of rapid expansion and evolving priorities.
• Background in marketing attribution or large-scale funnel analytics, bringing best practices in measuring conversion and impact across touchpoints.
• Previous work in EdTech, healthcare, or mission-driven organizations, where data is used to drive social good and operational excellence.

Practical notes

• The interview process includes an initial call, a hiring manager interview, a take-home assignment with a presentation, and an on-site panel interview.
• The company observes an open vacation policy with 15 days of PTO, 15 work-from-anywhere days, 10 public holidays for 2026, and a company-wide closure during the last week of December.
• Benefits include subsidized medical, dental, and vision insurance, 401(k), and FSA/HSA options.
• This role is based in New York City with a hybrid schedule requiring presence in the office on Tuesday, Wednesday, and Thursday.