Engineering Manager, Data
Engineering Manager · Manager · Full Time
Opens Stepful's application page
Role
What you'll do.
Engineering Manager, Data at Stepful leads the company's data infrastructure, analytics, and insights function while mentoring a team of three data professionals. You'll own end-to-end data platform operations—from pipelines and warehouses to business intelligence tooling—while remaining deeply hands-on with SQL, Python, and modern data stack technologies. This hybrid NYC-based role reports to the SVP of Engineering and partners across Growth, Product, Operations, and Finance to drive strategic decisions for a fast-growing healthcare workforce platform backed by Y Combinator and recently funded with $55M Series C.
Responsibilities
- Lead and Mentor Data Team: Lead, mentor, and develop a team of three data analysts and engineers, setting high standards for technical rigor, analytical craft, and professional growth. Foster a culture of continuous learning and ownership while managing performance and career development.
- Own Data Platform Architecture: Own Stepful's data platform end-to-end including data pipelines, data warehouse infrastructure, transformation layers, and business intelligence tooling. Ensure platform reliability, scalability, and performance as the company grows from 40,000+ student graduates and scales further.
- Define and Maintain Core Metrics: Define, establish, and maintain the company's core performance metrics across the student journey (enrollment, engagement, completion, certification, placement) and business KPIs (Customer Acquisition Cost, Lifetime Value, retention). Create single sources of truth for critical business metrics.
- Build Self-Serve Analytics Infrastructure: Design and develop dashboards and self-serve analytics capabilities that empower every team across the organization to access trustworthy, actionable data. Enable data democratization while maintaining data quality and governance standards.
- Drive Experimentation and A/B Testing: Partner closely with Growth and Product teams on experimentation strategy—design rigorous A/B tests, implement proper instrumentation, conduct statistical analysis, and deliver insights that inform product decisions and growth initiatives.
- Deliver Strategic Analyses: Conduct deep-dive analytical projects that shape strategic business decisions, from program curriculum design to budget allocation and market expansion strategy. Translate complex data findings into clear, actionable recommendations for executive leadership.
- Execute Hands-On Technical Work: Stay deeply hands-on writing production-quality SQL and Python code, implementing complex data transformations, and building analytical models. Review team code and technical work, and personally tackle the most challenging technical problems requiring deep expertise.
- Establish Data Governance and Quality Standards: Build and implement data governance frameworks, data quality practices, and documentation standards that scale with company growth. Ensure data lineage, validation, and compliance practices are robust and maintainable as organizational complexity increases.
Qualifications
What we look for.
Technical
Expert SQL Proficiency
Expert-level SQL skills with ability to write complex queries, optimize performance, and architect efficient data models. Proven track record of writing production SQL code across large datasets and handling complex analytical queries.
Strong Python Programming
Strong Python proficiency for data manipulation, statistical analysis, and building data applications. Experience with Python libraries such as Pandas, NumPy, Scikit-learn, and relevant data science frameworks.
Modern Data Stack Experience
Hands-on experience with modern data stack technologies including data transformation tools (dbt), cloud data warehouses (Snowflake, BigQuery), orchestration platforms (Airflow), and business intelligence tools (Looker, Metabase).
Data Pipeline and Warehouse Architecture
Experience designing, building, and maintaining scalable data pipelines and data warehouse architectures. Understanding of ETL/ELT processes, data modeling, dimensional modeling, and warehouse optimization.
Experimental Design and Statistical Analysis
Expertise designing and analyzing A/B tests and experiments in high-growth environments. Strong statistical knowledge including hypothesis testing, sample size calculations, statistical significance, and multiple comparison corrections.
Analytics and Business Intelligence
Proficiency in building self-serve analytics platforms and business intelligence dashboards. Experience with metrics definition, KPI tracking, and making data accessible to non-technical stakeholders.
Education
Bachelor's Degree in Quantitative Field
Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, Economics, Physics, or related quantitative field preferred. Equivalent professional experience may substitute for formal education.
Experience
7+ Years Data Industry Experience
Minimum 7 years of professional experience in data roles encompassing both analytics and data engineering disciplines, demonstrating breadth across the data spectrum.
2+ Years Team Leadership
Minimum 2+ years of experience managing and leading data teams. Proven success as a player-coach who sets direction and manages people while continuing to ship technical work independently.
High-Growth Environment Experience
Experience building or scaling data functions at early-stage or growth-stage startups where rapid iteration, resource constraints, and evolving business needs drive technical decisions.
Product and Business Acumen
Strong product thinking and business sense with ability to connect data work directly to business outcomes and strategic objectives rather than just delivering technical deliverables.
Skills
Required
SQL
Expert-level SQL for complex query optimization, data modeling, and analysis across large datasets in production environments.
Python
Strong Python programming for data manipulation, analysis, model building, and production data applications.
dbt (Data Build Tool)
Hands-on experience with dbt for data transformation, versioning, testing, and documentation in modern data workflows.
Snowflake or BigQuery
Proficiency with cloud data warehouse platforms for managing large-scale data storage, querying, and analytics.
Apache Airflow
Experience with Airflow for orchestrating complex data pipelines, scheduling jobs, and managing data workflows at scale.
BI Tools (Looker or Metabase)
Expertise building dashboards and self-serve analytics with Looker or Metabase for data visualization and stakeholder communication.
A/B Testing and Experimentation
Ability to design, implement, and analyze A/B tests with statistical rigor including hypothesis testing, statistical significance, and experimental best practices.
Team Leadership and Mentoring
Proven ability to lead, mentor, and develop data professionals while maintaining hands-on technical contributions and setting high quality standards.
Strategic Communication
Exceptional ability to translate complex technical and analytical findings into clear, actionable insights for non-technical stakeholders and executives.
Data Governance
Experience establishing data quality standards, governance frameworks, documentation, and best practices that scale with organizational growth.
Preferred
Marketing Attribution and Funnel Analytics
Nice to haveHands-on experience building marketing attribution models and analyzing conversion funnels at scale in high-growth environments.
EdTech or Healthcare Industry Experience
Nice to havePrior experience working in EdTech, healthcare, or other mission-driven industries with understanding of domain-specific metrics and business dynamics.
Startup Scaling Experience
Nice to haveExperience building or scaling data functions at early or growth-stage startups where you've handled evolving infrastructure needs with limited resources.
Student Outcomes Analytics
Nice to haveExperience analyzing student journey metrics including enrollment, engagement, completion, certification, and employment outcomes in educational platforms.
Advanced Statistical Modeling
Nice to haveExperience with predictive modeling, machine learning, causal inference, or advanced statistical techniques for business applications.
Data Cost Optimization
Nice to haveExperience optimizing data infrastructure costs, warehouse performance, and computational efficiency in cloud data environments.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 180,000 – 210,000
Equity·Stock options
Benefits
Meaningful Equity Stake
Competitive equity compensation providing meaningful ownership in Stepful's success. Recently funded with $55M Series C and backed by Y Combinator and prominent venture capital firms.
Comprehensive Health Coverage
Subsidized Medical, Dental, and Vision insurance plan options with multiple plan choices to fit individual and family needs.
Retirement and Tax Benefits
401(k) retirement plan, FSA (Flexible Spending Account), HSA (Health Savings Account), and commuter benefits for pre-tax transportation costs.
Flexible Time Off
Open vacation policy with guidance of 15 days PTO annually, plus 10 public holidays observed, 15 work-from-anywhere days, and company-wide closure the last week of December.
Hybrid Work Flexibility
Hybrid work arrangement based in NYC office with three days per week in-office requirement (Tuesday, Wednesday, Thursday), enabling work-life balance with remote flexibility.
Mission-Driven Culture
Work with a mission-driven team focused on solving healthcare workforce shortages and expanding opportunity for underserved communities in high-growth EdTech environment.
Process
Interview steps.
- 01
Initial Screening Call
Introductory conversation with Stepful's Talent Acquisition team member to discuss your background, motivation, understanding of the role, and assess initial fit with team and company culture.
- 02
Hiring Manager Interview
Technical and strategic conversation with the SVP of Engineering to discuss your leadership philosophy, technical depth, experience with data platform scaling, and vision for building high-performing data teams.
- 03
Take-Home Assignment and Presentation
Technical assessment involving a data analysis or data engineering challenge relevant to Stepful's business. You'll present your approach, findings, and recommendations to demonstrate analytical thinking, SQL/Python proficiency, and communication skills.
- 04
On-Site Panel Interview
Full-day or half-day on-site interview at Stepful's NYC office with panel of stakeholders including potential direct reports, cross-functional partners (Growth, Product, Operations, Finance), and senior leadership to assess team dynamics, technical capabilities, and organizational fit.
Full posting
Original listing.
About Stepful:
Stepful is a workforce platform redefining how America's largest health systems build, train, and retain their talent. Since our founding in 2021, Stepful’s trained over 32,000 practice-ready healthcare workers.
Layering onto our successful direct-to-consumer training, Stepful partners with leading healthcare institutions to address the growing national shortage of healthcare workers. We’re improving access to quality healthcare for everyone, everywhere, and improving access to healthcare career ladders for those who need them most.
Our students form the talent pipelines for major employers such as NY-Presbyterian, Mt. Sinai, HCA, Providence, CVS, and Walgreens. We have partnerships with half of the top 10 health systems in the US and are in process with many more.
Stepful is backed by Y Combinator, Reach Capital, and AlleyCorp, with a recent $55M Series C led by Oak HC/FT. We were named the #1 EdTech company in the U.S. by TIME for 2025.
Our values:
We credit much of our success to our exceptional team. We’re looking for mission-driven builders who thrive in fast-paced, ambiguous environments, and embody our four core values:
Care first: We do whatever it takes for our students to succeed.
Learn quickly: We test, learn with data, and iterate.
Build together: We win when we rely on each other.
Own it: We show up, take initiative, and show pride.
The opportunity:
We're hiring a Engineering Manager, Data to own Stepful's data function — the infrastructure, analytics, and insights that power decisions across the company, from student outcomes to marketing spend. You'll lead a team of three data analysts and engineers while staying deeply hands-on: writing code, building models, and shipping analyses alongside your team. As we scale past 40,000 students graduates, the leverage of great data work has never been higher.
This role reports directly to the SVP, Engineering and partners closely with Growth, Product, Operations, and Finance across the organization.
This is a hybrid opportunity based out of our NYC office, requiring three days/week (Tuesday, Wednesday, Thursday) in office.
What you'll do:
Lead, mentor, and grow a team of three data analysts and engineers, setting the standard for rigor and craft
Own Stepful's data platform end to end — pipelines, warehouse, transformation layer, and BI tooling — and its reliability and scalability
Define and maintain the company's core metrics across the student journey (enrollment, engagement, completion, certification, placement) and business performance (CAC, LTV, retention)
Build dashboards and self-serve analytics that put trustworthy data in every team's hands
Partner with Growth and Product on experimentation — design, instrumentation, and analysis of A/B tests
Deliver deep-dive analyses that shape strategic decisions, from program design to budget allocation
Stay hands-on: write production SQL and Python, review your team's work, and take on the hardest technical problems yourself
Establish data governance and quality practices that scale with the company
What you'll bring:
7+ years of data experience across analytics and data engineering, with at least 2+ years managing a team
Proven success as a player-coach — you set direction and manage people while still shipping your own work
Expert-level SQL and strong Python, with hands-on experience across the modern data stack (e.g., dbt, Snowflake/BigQuery, Airflow, Looker/Metabase)
Strong product and business sense — you connect data work to outcomes, not just deliverables
Experience designing and analyzing experiments in a high-growth environment
Exceptional communication skills with the ability to make complex findings clear to non-technical stakeholders
Bonus points if:
You've built or scaled a data function at an early or growth-stage startup
You've worked with marketing attribution or funnel analytics at scale
You've worked in EdTech, healthcare, or another mission-driven industry
Interview Process:
Introductory call with Talent Acquisition team member
Interview with Hiring Manager
Take-Home Assignment and Presentation
On-Site Panel Interview
Benefits and Compensation:
Meaningful Equity Stake
Subsidized Medical, Dental, and Vision insurance plan options
401(k)
FSA, HSA and commuter benefits
Open vacation policy, including:
Guidance of 15 days PTO annually
Stepful closed the last week of December
15 work-from-anywhere days
10 public holidays observed for 2026
The target base salary range for this opportunity is $180,000 - $210,000, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, internal pay equity and other relevant business considerations.
Stepful is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic.
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