Lead Engineer, Analytics Platform & AI
Lead Engineer, Analytics Platform & AI
Posted 39 days ago
SENIORITY
Manager
About the role
- Full 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.
- 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
Before you apply
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Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
