Software Engineer, Data Platform at Xealth

Seattle, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

12 Oct, 26

Salary

175000.0

Posted On

14 Jul, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Distributed Systems, Data Modeling, Data Pipelines, AWS, Kubernetes, Delta Lake, Apache Parquet, Apache Avro, RESTful APIs, Infrastructure as Code, Unit Testing, Integration Testing, SOLID Principles, Clean Architecture

Industry

Hospitals and Health Care

Description

Our Mission & Culture At Xealth, we're revolutionizing healthcare by leveraging data and automation to empower care providers (building on EHRs such as Epic and Cerner) to seamlessly prescribe, deliver, and monitor digital health for patients. We are a detail-oriented team, committed to maintaining the highest standards while moving with agility and impact. We are a highly skilled, collaborative, and passionate group, applying our expertise to improve health outcomes for millions. We believe in shared ownership and are looking for a team player who is a self-starter and self-driven to pioneer the next generation of intelligent, automated cloud infrastructure. This role offers a unique opportunity to join a data engineering team to advance our capabilities with data processing pipelines and our analytics product offering. *This position is a hybrid role, working from our Seattle office. Please note - you MUST be a U.S. Citizen or Permanent Resident to be hired* What You'll Own and Deliver (Responsibilities) As a software engineer on our data platform team, you will design and build scalable systems, write maintainable and well-tested code, and own end-to-end engineering quality across the services that drive Xealth's Analytics and Reporting Capabilities. You’ll apply solid computer science fundamentals to solve complex problems in distributed systems, data modeling, and data pipelines. System & Architecture Design: Design scalable, maintainable systems for high-volume data processing. Build robust abstractions and well-structured APIs that other engineers can build on with confidence. Data Ingestion: Ability to consume and process high-volume bounded and unbounded data, manage real-time data streams, and gather data from API calls and webhooks. Scalability & Maintenance: Maintain and scale large Data Lake Pipelines, ensuring high performance and cost-efficiency. Performance & Optimization: Profile, debug, and optimize systems for performance and cost. Identify and remove bottlenecks across distributed workloads. Unit testing & Quality Assurance: Write comprehensive unit and integration tests for data pipelines to ensure code quality and production reliability. Cross-Functional Collaboration: Partner with product managers and EHR specialists to translate clinical user behaviors into rich, analytical datasets, unlocking critical insights that drive evidence-based improvements in healthcare processes. Documentation: Produce clear technical documentation — design docs, architecture decisions, and system references that keep knowledge shared and durable. AI-Assisted Development: Use AI-assisted coding tools (e.g., Claude, GitHub Copilot) to accelerate delivery and raise quality, and help the team adopt effective agentic workflows. The Expertise You'll Bring (Requirements) Must Have: We’re looking for a data engineer with strong computer science fundamentals — someone who’s comfortable reasoning about systems, data, and code structure at scale, and who’s excited to apply those skills in healthcare. Core Technical Competencies Software Engineering Fundamentals: 3+ years building production software, with strong command of SOLID principles, design patterns, and clean architecture. You care about code quality and know how to make it stick through review and testing. CS Fundamentals: Deep understanding of algorithms and data structures, with a specific focus on distributed computing principles (concurrency, partitioning, shuffling) necessary for processing large-scale datasets. Testing Practices: Fluency across unit, integration, and end-to-end testing. You design for testability and treat automated tests as core to shipping. Languages: Strong proficiency in Python and SQL; ability to pick up new languages and frameworks quickly. Familiarity with JavaScript is a plus. Modern SQL and Non-SQL Database Design: Deep practical knowledge of open table formats, such as Delta Lake. Proficiency with common big data file formats, including Apache Parquet and Apache Avro. Infrastructure as Code (IaC): Experience implementing IaC principles and tools for the automated deployment and management of data pipelines. API & Integration: Hands-on experience designing robust data ingestion frameworks via RESTful APIs and building event-driven architectures for real-time data flow. Cloud & Distributed Systems: Experience designing and scaling cloud-native data platforms and orchestrating data workloads using AWS and Kubernetes. Collaboration and Agility: Comfortable working in an agile startup environment, balancing quality with rapid iteration. Highly Valued Experience (Nice to Have) Agentic Systems & LLM Integration: Experience with agentic systems, Claude/LLM integration, or AI-assisted development workflows Observability: Experience implementing observability, monitoring, and tracing for production systems. Data Systems Depth: Familiarity with open table formats (e.g., Delta Lake), big data file formats (Parquet, Avro), or stream processors (Kafka, Flink). Security & Governance: Prior experience in a regulated, high-security industry, with a working understanding of data security principles — particularly around Protected Health Information (PHI). Why Join Xealth? Meaningful Work: Your engineering directly enables better patient care and health outcomes for millions. Cutting-Edge Stack: Work with modern tools and a team that prioritizes technical excellence and continuous learning. About Xealth Xealth created the leading digital health platform helping health systems deliver connected, personalized care at scale. Embedded in the EHR, it enables clinicians to prescribe, automate, and measure the impact of digital tools--including apps, services, and wearable data--within existing workflows. Now part of Samsung's connected care vision, Xealth enhances decision-making, reduces friction, and supports enterprise-wide digital health strategies. Trusted by more than 500 hospitals and 70+ solution partners, Xealth provides a scalable foundation for delivering connected, personalized, and preventative care--empowering health systems to drive outcomes, engagement, and operational efficiency while advancing digital transformation. As a market-leading digital health platform recognized for excellence and culture, some of our recent accolades include: Newsweek’s World’s Best Digital Health Companies (2024-2026), consecutive Gold Digital Health Awards, and we were named a BuiltIn Best Place to Work for 2025 and 2026. Compensation and Benefits: Xealth offers a multi-tiered approach when constructing a highly competitive compensation package. The compensation package would include a base salary, bonus, and a comprehensive suite of benefits. The base salary compensation range for this position is $150,000 - $175,000, depending on geographic market. Paid parental leave. Comprehensive medical, dental, and vision policies. Xealth covers 100% of employee premiums. We also provide Employee Assistance Programs. Xealth provides your laptop and offers a home office stipend. Generous learning & development opportunities for you to grow your skills and career. 401k Match: Xealth offers a dollar-for-dollar match up to 5%. Flexible time off & 10 standardized holidays. $500 yearly fitness stipend to spend on staying active. Xealth is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. #LI-DNI

Responsibilities

Design and build scalable systems and data pipelines to drive analytics and reporting capabilities. Collaborate with cross-functional teams to translate clinical behaviors into analytical datasets while maintaining high engineering quality.