Senior Software Engineer, Pomelo Care

• You have significant experience (5+ years) in data engineering or backend engineering with a strong data focus
• You've built and maintained data pipelines and models that other teams depend on daily
• You care deeply about data quality, and you understand why "good enough" data can be dangerous in the wrong context
• You're comfortable with modern data tooling (dbt, Dagster, or similar) and cloud data infrastructure
• You're keeping up with trends in LLM coding agents to multiply your engineering impact
• You enjoy working across teams and translating technical data concepts into terms that product and clinical folks can work with

Desirable

• This role sits at the center of product, clinical care, and operations, enabling smarter workflows and better outcomes for patients
• You'll work on problems where data quality and clarity directly affect real-world healthcare decisions. It's a chance to shape the foundation that future AI and product innovation will build on, while seeing your work immediately impact how the company operates
• Build and scale the data foundation that powers decision-making and product experiences across Pomelo
• Lead the design of robust pipelines, data models, and infrastructure that reduce time-to-insight for clinical, product, and operational teams
• Translate messy real-world healthcare data into reliable, accessible datasets that enable analytics, experimentation, and new data-driven features
• Help raise the bar for data engineering practices and mentor others on building scalable, maintainable systems
• Work closely with product, clinical, and engineering teams to power both internal insights and customer-facing features
• Problems You'll Dig Into:
• How do we turn complex clinical and operational data into something trustworthy and actionable at scale?
• How do we design data systems that support both analytics and product use cases without creating duplication or fragility?
• How do we balance speed and iteration with correctness and governance in a healthcare environment?
• How do we reduce the gap between raw data and real decisions so teams can move faster?
• How do we evolve our data platform as AI and automation become more central to how we operate?
• Tech Stack:
• Python, Kotlin, modern cloud data infrastructure, SQL. dbt, Dagster, Beam, Dataflow, analytics and experimentation tooling, data warehouses, orchestration and observability tools