Senior Manager, Data Engineering

At Fuze Health, we put patients first and tirelessly address the most pressing needs in healthcare. We empower millions to digitally connect with care providers, essential health resources and needed treatments – and enable care providers, employers, health plans and life sciences companies to meaningfully enhance quality, outcomes and value. We are dedicated to helping our partners evolve and modernize to meet emerging patient and marketplace needs. Fuze Health’s foundation is built upon the strategic combination of several proven, technology-powered innovators in the digital health, diagnostics, and pharmacy sectors. Data is foundational to how we serve patients, empower operators, and enable smarter decision-making across the business. As the Senior Manager, Data Engineering, you will lead the strategy, architecture, and execution of Alto’s data platform — ensuring that high-quality, trusted, and timely data fuels everything from analytics and operations to product innovation and machine learning. You will manage, build and lead a high-performing team responsible for designing resilient data pipelines, evolving our modern data stack, and establishing data engineering best practices. This role is equal parts technical leadership, organizational design, and cross-functional partnership — shaping how data is produced, governed, and consumed across a fast-growing, technology-driven healthcare organization. Lead, mentor, and grow a team of Data Engineers, fostering a culture of ownership, technical excellence, and continuous improvement. Define and execute the long-term vision for Alto’s data platform, ensuring alignment with company strategy and product roadmaps. Partner with Product, Engineering, Data Science, Analytics, Finance, and Enterprise teams to prioritize and deliver high-impact data initiatives. Establish clear career paths, performance standards, and hiring plans to scale the team thoughtfully and sustainably. Build strong stakeholder trust by translating business needs into scalable data solutions. Data Platform & Architecture Own the design and evolution of Alto’s data architecture, including ingestion, transformation, orchestration, storage, and serving layers. Administer and maintain core platform tooling — including Fivetran, Airflow, dbt, Snowflake, and Looker — ensuring these systems operate as reliable, scalable, and secure infrastructure. Provide a robust, well-governed platform foundation that enables Analytics to build and manage transformation logic within dbt, while enforcing standards for performance, testing, deployment workflows, access controls, and warehouse efficiency. Ensure the underlying data platform reliably powers analytics, operational workflows, experimentation, and machine learning use cases — delivering trusted, well-documented, and production-grade data assets to both internal stakeholders and downstream systems. Ensure the reliability, performance, and freshness of data pipelines through strong observability, lineage tracking, testing frameworks, and operational rigor. Scale the platform to support increasing data volume, near-real-time use cases, and expanding business and regulatory complexity. Data Governance, Quality & Operational Excellence Evolve and strengthen existing standards for data governance, access control, privacy, and compliance within a regulated healthcare environment. Refine and operationalize SLAs and performance metrics for data pipelines and platform reliability, ensuring clear accountability and transparency. Enhance and scale current data quality monitoring and incident management practices to improve resilience, observability, and response times. Continuously optimize infrastructure performance and cost efficiency through thoughtful architectural improvements and warehouse tuning. Evaluate emerging technologies and evolve Alto’s data stack to support streaming, near-real-time analytics, and scalable AI workflows. Enable robust experimentation and measurement by providing reliable, well-instrumented, and production-grade data pipelines that Analytics, Data Science, and Product teams can confidently build upon. Collaborate closely with Data Science and Machine Learning teams to ensure the platform scales alongside growing model and feature complexity, providing the infrastructure, environment consistency, and operational guardrails necessary for reliable training and production inference. Cultivate a culture where data is treated as a product — with clear ownership, discoverability, and accountability. Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field; 10+ years of experience in data engineering, platform engineering, or related data infrastructure roles. Proven experience architecting, operating, and scaling modern cloud-based data platforms, including data ingestion, orchestration, cloud data warehouses, transformation frameworks, and semantic serving layers. Strong expertise in data modeling principles, ELT architectures, and production-grade pipeline orchestration. Hands-on experience with cloud environments (AWS, GCP, or Azure). Proven track record owning platform reliability, including defining SLAs, implementing observability and data quality frameworks, and leading incident response and postmortems for production data systems. Experience building data platforms in healthcare, pharmacy, fintech, or other regulated industries. Familiarity with HIPAA and healthcare data privacy standards. Experience supporting machine learning pipelines, feature engineering workflows, or feature stores. Exposure to experimentation platforms and product analytics ecosystems. Strong SQL and programming proficiency (e.g., Python, Scala, or similar). Experience implementing data contracts and data product frameworks across domain teams. Physical requirements for this role include the ability to work at a computer terminal with monitor, keyboard and mouse for extended periods of time, stoop, bend, and reach for equipment and supplies, make frequent repetitive motions required to operate a computer that include the wrists, hands and fingers, and lift, carry, push, pull, and move light objects up to 20 pounds. Consistent with the Americans with Disabilities Act (ADA) and similar applicable state laws, it is Fuze Health’s policy to provide reasonable accommodation to enable qualified individuals with disabilities to perform essential job functions, unless such accommodation would cause an undue hardship. Incentive/Bonus Eligible: No Equity Eligible: Yes Benefits: Full-time employee benefits include: dental, vision, and multiple group medical plans to choose from, a 401(k) retirement savings plan, group life insurance, accidental death and dismemberment (AD&D) insurance, flexible spending account (FSA) and health savings account (HSA), commuter benefits, employer-paid short-term (STD) and long-term disability (LTD) insurance, and additional supplemental insurance plans (spouse life insurance, legal insurance, an employee assistance program, home health testing kits, and a fertility medication discount program). Employees are also provided flexible vacation time, accrued paid sick time, 10 paid holidays, (2 floating holidays for full time non-exempt employees) , and eight weeks of paid parental leave for eligible employees, additional paid weeks for the birthing parent, 4 weeks paid caregiver leave, and a Lifestyle Spending Account allowance each month. More Benefits Information Here: Fuze Health Benefits Site #LI-Remote All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, gender identity, sexual orientation, age, disability, veteran status, or any other legally protected basis. If you have a disability and require reasonable accommodation during any portion of the application or hiring process, please contact us at are an E-Verify participating company. Fuze Health recruiters and hiring managers may use automated decision tools to help identify candidates who match the stated job requirements, and to what extent. These tools are designed to help ensure fairness in all aspects of the hiring process by providing recruiters and hiring managers with data-backed insights based on information provided in your resume, including work experience, education, and other skills. #J-18808-Ljbffr