Job Title: Principal Data Architect / Lead Data Platform Architect / Enterprise Data Architect / Solutions Architect – Data Engineering

About Company:

The healthcare industry is the next great frontier of opportunity for software development, and Health Catalyst is one of the most dynamic and influential companies in this space. We are working on solving national-level healthcare problems, and this is your chance to improve the lives of millions of people, including your family and friends. Health Catalyst is a fast-growing company that values smart, hardworking, and humble individuals. Each product team is a small, mission-critical team focused on developing innovative tools to support Catalyst’s mission to improve healthcare performance, cost, and quality.

Health Catalyst is expanding and maintains a large suite of Improvement Apps that contribute to healthcare analytics and process improvement solutions. This includes products that manage the care of health system populations, better serve patients at the point of care, reduce health system costs, and reduce clinician workload.

Job Overview

We are seeking a seasoned Principal Data Architect to design, implement, and maintain scalable data ingestion and processing systems for healthcare and clinical data pipelines. This role is ideal for someone who thrives in building real-time data platforms using Kafka, microservices, and distributed systems on AWS. You will lead architectural decisions, influence data governance practices, and support systems that process billions of patient records daily.

Key Responsibilities

• Architect and lead the development of scalable, secure, and high-performance data platforms on AWS.
• Own and optimize Kafka-based pipelines handling real-time and batch ingestion of clinical data (HL7v2, CCDA).
• Design and manage Kafka Connect infrastructure with custom SMTs and JDBC, S3, MongoDB, and OpenSearch connectors.
• Implement fault-tolerant systems using DLQs, Prometheus, Grafana, and CloudWatch for observability and alerting.
• Drive deduplication strategies and stream processing (Kafka Streams, Flink) to reduce downstream load.
• Collaborate with parser teams to optimize Java-based services that convert HL7 and CCDA into structured data for Kafka brokers.
• Define and enforce data quality and governance best practices across the pipeline.
• Provide mentorship and technical leadership to a team of engineers and data professionals.
• Engage with product, compliance, and analytics teams to align the data platform with broader business goals.

Required Qualifications

• 9+ years of experience in software/data engineering with a focus on distributed systems.
• Expertise in Kafka ecosystem (brokers, Kafka Connect, Streams, Schema Registry).
• Deep knowledge of AWS services (EC2, S3, RDS, CloudWatch, IAM, MSK, etc.).
• Strong Java development skills; familiarity with multithreading, concurrency, and system design patterns.
• Experience with microservices, Docker, and CI/CD pipelines.
• Proficiency with clinical data formats like HL7v2 and CCDA.
• Experience in performance tuning large-scale data systems (billions of records/day).
• Knowledge of database technologies: MySQL/PostgreSQL, MongoDB, Snowflake, Cassendra, DynamoDB
• Excellent communication skills and ability to work cross-functionally.

Preferred Qualifications

• Experience with Flink or Spark for streaming and batch processing.
• Knowledge of FHIR, HIPAA compliance, and healthcare domain challenges.
• Experience with Confluent Kafka
• Background in data deduplication strategies, ETL optimizations, and distributed caching.
• Familiarity with Agile and Scrum methodologies.