[Remote] Senior Data Engineer
Note: The job is a remote job and is open to candidates in USA. 9amHealth is an AI-enabled virtual specialty care platform focused on managing high-cost chronic conditions at scale. They are seeking a Senior Data Engineer to own and evolve the data platform that powers clinical operations, business intelligence, and AI initiatives.
Responsibilities
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows in Python using AWS Glue, Apache Spark, Airflow, or equivalent orchestration tools
- Write production-grade Python code for DWH logic, reporting jobs, data transformations, and internal tooling, following software engineering best practices (testing, code review, CI/CD)
- Develop and optimize analytical data models (dimensional, OBT, or hybrid) that serve self-service BI and advanced analytics use cases
- Build and maintain dashboards, explores, and semantic layers in Looker and/or Tableau; serve as the analytics infrastructure owner ensuring data quality and governance
- Contribute backend application code in Java (Spring Boot) or Python to support data-intensive features, API integrations, and internal services
- Champion modern AI coding practices across the data team, leveraging tools like GitHub Copilot, Claude, Cursor, or similar AI-assisted development environments to accelerate delivery and code quality
- Author and maintain comprehensive SQL assets (stored procedures, views, complex queries) across Redshift, Aurora/MySQL, and Athena
- Operate and optimize AWS data infrastructure including Glue, S3, Redshift, CloudFormation, CloudWatch, IAM, and Athena
- Collaborate closely with clinical operations, product, finance, and engineering teams to translate business questions into reliable, well-documented data products
- Implement data quality frameworks, monitoring, alerting, and incident response processes for the data platform
- Contribute to the architecture and data strategy for AI/ML features, including data prep, feature engineering, and model monitoring
- Mentor the existing data analyst and data engineer; help establish team standards, code review practices, and documentation norms
Skills
- 10+ years of professional experience in data engineering, analytics engineering, or a hybrid data/backend software engineering role
- Strong software engineering background: this role requires someone who can write, test, debug, and ship production code, not just query data
- Expert-level Python: deep experience building production data pipelines, ETL logic, and reporting systems in Python
- Expert-level SQL: window functions, CTEs, recursive queries, query optimization, and performance tuning at scale
- Hands-on experience with AWS data services, specifically Glue, S3, Redshift, Athena, CloudFormation, CloudWatch, and IAM
- Experience with MySQL/Aurora in a production environment
- Hands-on experience building and operating data pipelines with AWS Glue, Spark, dbt, Airflow, or comparable frameworks
- Deep experience with at least one modern BI platform. Looker (LookML) strongly preferred; Tableau also valued. Should include semantic modeling, dashboard design, and self-service enablement
- Solid understanding of data modeling techniques: star/snowflake schemas, slowly changing dimensions, event-based models
- Familiarity with AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, Cody) and a demonstrated interest in integrating AI into engineering workflows
- Proficiency in Java (Spring Boot, Maven/Gradle) with experience shipping backend services or data-intensive applications to production
- AWS certifications (e.g., Solutions Architect, Data Analytics Specialty, or Database Specialty)
- Experience in health tech, digital health, or regulated industries (HIPAA familiarity is a plus)
- Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar)
- Background in building or contributing to AI/ML features: feature stores, training pipelines, model serving, or RAG architectures
- Comfort with infrastructure-as-code (Terraform, CloudFormation) and containerized deployments (Docker, ECS/EKS)
- Prior experience in a startup or high-growth environment where you owned outcomes end to end
- Track record of improving developer experience and productivity through tooling, automation, or process improvements
Benefits
- Health, dental, and vision insurance
- Flexible PTO
- Work from home options
- Professional development budget
- Support continuing education
Company Overview