Senior Software Engineer, Core Data

About us Pomelo Care is the national leader in evidence-based healthcare for women and children. We deliver personalized, high-quality clinical interventions from reproductive care and pregnancy, infant care and pediatrics, to hormonal health through perimenopause and menopause, with long-term preventive care and condition management. Our model delivers 24/7 multispecialty care to address the medical, behavioral, and social factors that most significantly impact outcomes for women and children. We partner with payers, employers, and providers to expand access to quality healthcare across the system. Our engineering team is the engine behind our virtual care platform, building AI-powered solutions that transform care delivery and create exceptional experiences for both patients and clinicians. If you're passionate about using technology to do real, tangible good in the world, we'd love to meet you. We are a remote-first company with offices in New York and San Francisco. Our New York office has a strong in-person culture with regular collaboration, and our San Francisco office is available for those who enjoy working together in person. Why This Role Matters Data is a force multiplier at Pomelo. When the data platform improves, every team moves faster and makes better decisions. 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. What You'll Do 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. Who You Are 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 We'll be especially excited if you: Have experience working with healthcare data (clinical, claims, EHR) and understand the unique challenges it presents Have built data platforms that serve both analytical and product use cases Have experience with experimentation infr ... (truncated, view full listing at source)