Market Insights is Huron's analytics product suite, built on a foundation of tens of billions of medical claims, millions of clinical providers, and hundreds of millions of unique patient lives. We are looking for a Full Stack Lead Engineer to guide the technical direction of this platform end to end, from the data layer through the user interface, with a mandate to embed AI directly into how our analytics products are built and how they deliver insight to clients.
This is a hands on leadership role. You will write and review code, set architecture and technical standards, and lead a team of engineers, while partnering closely with product management, data engineering, and data science to bring intelligent, AI enabled analytics capabilities to market faster.
ResponsibilitiesFull stack product development- Lead design and development across the stack: responsive front end interfaces, APIs and services, and the underlying data layer for analytics products.
- Set technical direction and architecture for scalability, security, and performance of AWS based analytics solutions.
- Collaborate with product management on roadmap, prioritization, and feature delivery using Agile practices.
AI and machine learning in analytics- Identify and lead opportunities to embed AI and Agentic AI capabilities into analytics products: predictive models, natural language interfaces over data, automated insight generation, and generative AI features that help clients act faster on their data.
- Partner with data scientists to move machine learning models from prototype into reliable, production grade services.
- Evaluate and apply large language model based tools where they add measurable client value, with attention to data privacy, accuracy, and healthcare compliance requirements.
Data engineering- Design and maintain ETL and data pipeline processes that feed dashboards, models, and client facing reporting.
- Work with cloud data services, including S3, Redshift, Glue, Lambda, and Athena, to build scalable data infrastructure.
- Uphold data governance, quality, and healthcare data handling standards across the platform.
Team leadership- Support, and mentor a team of engineers, providing technical guidance and career development.
- Establish and continuously improve engineering practices, code quality standards, and delivery processes.
- Communicate progress, risks, and technical decisions clearly to product leadership and cross functional stakeholders.
QualificationsRequired:
- 8 or more years of professional software engineering experience, including full stack development across both front end and back end technologies.
- 3 or more years leading or mentoring engineers, formally or informally.
- Demonstrated experience applying AI or machine learning within a production analytics or data product, such as predictive modeling, recommendation systems, or generative AI features.
- Strong front end development skills in TypeScript, JavaScript, and React.
- Strong back end skills in Python, and an equivalent language used for analytics and API development.
- Solid understanding of relational databases and SQL.
- Working knowledge of core AWS services relevant to data and analytics, including Lambda, IAM, S3, Redshift, Glue, and Athena.
- Experience with infrastructure as code using AWS CloudFormation and the AWS CDK.
- Experience with version control systems, particularly Git.
- Experience delivering software using Agile methodologies.
- Excellent written and verbal communication skills, with the ability to explain technical tradeoffs to non-technical stakeholders.
Preferred:
- Familiarity with healthcare data interoperability standards, such as ANSI X12, HL7, and FHIR.
- Experience with healthcare claims data is a plus.
- Hands on experience with large language models, prompt engineering, retrieval augmented generation, or vector databases.
- Experience with MLOps practices for deploying and monitoring machine learning models in production.
- Experience with SQLAlchemy and PostgreSQL.
- Experience with row based databases such as Amazon RDS and Aurora.
- Experience with columnar or data warehouse platforms such as Redshift, Athena, and Snowflake.
- Experience with NoSQL databases such as DynamoDB.
- Experience with a broader range of AWS services beyond the core set, and with Azure DevOps for build and release pipelines.
- Experience with big data technologies such as Spark, or infrastructure as code tools such as Terraform.
- Background in healthcare or higher education analytics.
- AWS certification, such as AWS Certified Solutions Architect or AWS Certified Developer.
- A bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience.
Position LevelSenior Associate
CountryUnited States of America
