Software Engineer, Data Platform

Xealth•Seattle, WA

3d•$150,000 - $175,000•Hybrid

About The Position

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

Requirements

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.
3+ years building production software, with strong command of SOLID principles, design patterns, and clean architecture.
Deep understanding of algorithms and data structures, with a specific focus on distributed computing principles (concurrency, partitioning, shuffling) necessary for processing large-scale datasets.
Fluency across unit, integration, and end-to-end testing. You design for testability and treat automated tests as core to shipping.
Strong proficiency in Python and SQL; ability to pick up new languages and frameworks quickly.
Deep practical knowledge of open table formats, such as Delta Lake.
Proficiency with common big data file formats, including Apache Parquet and Apache Avro.
Experience implementing IaC principles and tools for the automated deployment and management of data pipelines.
Hands-on experience designing robust data ingestion frameworks via RESTful APIs and building event-driven architectures for real-time data flow.
Experience designing and scaling cloud-native data platforms and orchestrating data workloads using AWS and Kubernetes.
Comfortable working in an agile startup environment, balancing quality with rapid iteration.
Must be a U.S. Citizen or Permanent Resident.

Nice To Haves

Familiarity with JavaScript.
Experience with agentic systems, Claude/LLM integration, or AI-assisted development workflows.
Experience implementing observability, monitoring, and tracing for production systems.
Familiarity with stream processors (Kafka, Flink).
Prior experience in a regulated, high-security industry, with a working understanding of data security principles — particularly around Protected Health Information (PHI).

Responsibilities

Design scalable, maintainable systems for high-volume data processing.
Build robust abstractions and well-structured APIs that other engineers can build on with confidence.
Consume and process high-volume bounded and unbounded data, manage real-time data streams, and gather data from API calls and webhooks.
Maintain and scale large Data Lake Pipelines, ensuring high performance and cost-efficiency.
Profile, debug, and optimize systems for performance and cost. Identify and remove bottlenecks across distributed workloads.
Write comprehensive unit and integration tests for data pipelines to ensure code quality and production reliability.
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.
Produce clear technical documentation — design docs, architecture decisions, and system references that keep knowledge shared and durable.
Use AI-assisted coding tools (e.g., Claude, GitHub Copilot) to accelerate delivery and raise quality, and help the team adopt effective agentic workflows.