Join a pioneering health technology company dedicated to transforming how people manage their well-being through AI-driven solutions. With a mission to make healthcare more accessible, proactive, and personalized, they leverage cutting-edge technology to empower individuals with real-time health insights and support. Their innovative platform is designed to enhance user engagement and improve health outcomes at scale.
We are looking for a technical and hands-on Data Engineering Manager to lead the design and development of our data infrastructure, pipelines, and modeling frameworks. You will be responsible for enabling real-time and batch data workflows that power analytics, clinical insights, AI capabilities, and product experiences. This is a key leadership role reporting directly to the VP of Engineering and collaborating closely with data analysts, data scientists, and cross-functional engineering teams.
What You'll Do
- Lead the design, implementation, and scaling of our data infrastructure across the company, including ETL/ELT pipelines, warehouse design, and data governance.
- Own the data modeling strategy for analytics and operations, balancing business needs with long-term maintainability.
- Guide architecture decisions and hands-on development in modern data stacks, including Snowflake, dbt, and cloud-native solutions (e.g., AWS).
- Manage and mentor a small but growing team of data engineers, fostering a culture of high performance, collaboration, and technical excellence.
- Ensure data reliability, integrity, lineage, and observability across the stack.
- Collaborate with analytics, AI/ML, and product teams to build foundational datasets and services for decision-making, reporting, and intelligent features.
- Drive engineering best practices (testing, CI/CD, documentation, cost optimization) for data infrastructure.
- Contribute to and review code, especially for complex data workflows or infrastructure changes.
- Lead infrastructure modernization and performance tuning projects (e.g., event streaming, real-time ingestion, or hybrid data architectures).
- Allocate at least 60% of time to hands-on coding, architecture design, and critical incident resolution alongside the team.
- Evaluate and introduce AI-enhanced engineering tools where relevant (e.g., for pipeline monitoring, schema validation, or data anomaly detection).
What You Need
- 10+ years of experience in data engineering or backend infrastructure roles.
- 3+ years managing engineering teams with a strong track record of execution and technical leadership.
- Deep expertise in data modeling, ETL/ELT architecture, and building robust data platforms.
- Proficient in SQL, Python, and tools like dbt, Airflow, and Snowflake (or similar cloud warehouses).
- Strong background in cloud-native data architecture, preferably on AWS.
- Comfortable working hands-on and guiding team members through technical deep-dives.
- Demonstrated ability to collaborate across engineering, data, and business functions.
- Experience building for analytics, operations, and AI/ML teams.
- Preferred Experience:
- Strong preference for candidates with hands-on experience in healthcare data platforms, clinical data integration, or HIPAA/SOC 2 compliance.
- Experience with event-driven architecture and real-time data processing.
- Prior work in high-growth startups or regulated environments.
Salary & Benefits
- Location: Hybrid in Seattle, WA.
- Salary: $160,000 - $190,000 / Year.
- This is a full-time, long-term position.
- The position is immediately available.
- Hybrid.
- Monday through Friday.
- High-Impact Role: Own a core growth channel in a sector of healthtech experiencing rapid growth.
- Mission-Driven: Join a company that’s improving patient outcomes and transforming the way healthcare is delivered.
- Fast-Growing Environment: Thrive in a dynamic, scale-up atmosphere where you’ll have the autonomy to create meaningful change and implement new ideas from day one.
- Cutting-Edge Tech: Work with innovative tools and have the freedom to introduce new solutions, including AI-driven approaches.
- Collaborative Culture: Partner with passionate teams in Marketing, Product, and Clinic Ops to drive measurable results.
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