Senior Manager, Data Engineering

About the role

You will define and lead the technical strategy for Headway's data infrastructure as a Senior Manager, Data Engineering, owning the end to end design of systems that power analytics, machine learning, and operational decision making across the organization. This role is mission critical because you will build and maintain the reliable, scalable data platforms that serve over 75,000 providers and more than 1 million patients nationwide. You will partner deeply with Data Science, Analytics, Product, and Engineering teams to anticipate data needs and turn them into robust, production grade solutions. Your work will directly support the company mission to fix mental healthcare access by making the admin infrastructure invisible and the care experience seamless. You will own the architecture and evolution of core data platforms, ensuring trustworthiness, performance, and scalability as the business grows rapidly. The role requires you to balance strategic technical vision with hands on engagement, surfacing risks early and guiding decisions from design through launch and iteration. You will translate complex data initiatives into clear, actionable recommendations for executives while mentoring engineers to uphold craftsmanship and ownership.

Key facts

What you'll do

Lead and grow a high performing team of Data Engineers, fostering a culture of technical excellence, ownership, and continuous learning.

Develop quarterly roadmaps in close collaboration with Data Science, Operations, and Engineering partners, aligning data resources and overseeing timely, high quality execution.

Own the architecture, reliability, and scalability of Headway's data platform, encompassing the data warehouse, ingestion pipelines, transformation layer (dbt), and orchestration systems.

Define and champion engineering standards, including data modeling conventions, pipeline observability, SLA frameworks, and data quality monitoring practices.

Partner cross functionally to design and build the data infrastructure that powers analytics, experimentation, machine learning models, and operational tooling at scale.

Engage directly with strategic technical challenges to surface gaps in platform capabilities before they turn into bottlenecks for growth.

Translate intricate data decisions into clear, executive friendly recommendations that influence strategic direction and resource allocation.

Implement robust data quality frameworks that ensure accuracy, consistency, and trust across all datasets used for care operations and compliance.

Optimize pipeline performance and cost efficiency in a high growth, cloud native environment, balancing speed, reliability, and infrastructure economics.

Establish incident response and monitoring practices that minimize downtime and enable rapid troubleshooting of data issues.

Drive adoption of best practices for version control, testing, and documentation across data engineering workflows.

Collaborate with security and privacy teams to ensure data handling meets regulatory requirements and internal governance policies.

Mentor engineers through code reviews, technical guidance, and career development, building a strong, cohesive data engineering organization.

Evaluate emerging tools and technologies, running experiments to validate improvements before large scale rollout.

Requirements

Bring 8 or more years of professional experience in data engineering or closely related roles, demonstrating depth in building data platforms.

Show 3 or more years of experience managing and developing teams, including hiring, performance feedback, and career growth conversations.

Have a proven track record of building and scaling data platforms within high growth, cloud native environments, with comfort operating in fast moving, ambiguous situations.

Demonstrate a history of successful cross functional partnership with Data Science, Analytics, and Product Engineering to deliver impactful data solutions.

Possess deep expertise in data warehouse design, pipeline architecture, and modern transformation frameworks such as dbt, with the ability to coach others through complex trade offs.

Hold strong opinions on data modeling, schema design, and dimensional modeling principles, and communicate those clearly to both technical and non technical audiences.

Have experience implementing observability, monitoring, and alerting for data pipelines, including metrics around latency, throughput, and error rates.

Understand compliance and security considerations relevant to healthcare data, including privacy, auditability, and controlled access.

Nice to have

Experience with managed data platforms in major cloud providers, including provisioning, networking, and cost optimization.

Background working with regulated industries and familiarity with healthcare specific data constraints.

Contributions to open source data projects or public sharing of technical learnings through writing or talks.

Practical notes

The expected base pay range for this position is $212,000 - $265,000, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

Equity compensation

Medical, Dental, and Vision coverage

HSA / FSA

401K

Work-from-Home Stipend

Therapy Reimbursement

16 week parental leave for eligible employees

Carrot Fertility annual reimbursement and membership

13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st

Flexible PTO

Employee Assistance Program (EAP)

Training and professional development