Senior Data Engineer

About the role

We are looking for a Senior Data Engineer to join our lean, high-impact Data & Analytics team (currently a data analyst and a data engineer).

Responsibilities

• Own and evolve the data platform that powers clinical operations, business intelligence, and AI initiatives.
• Build and maintain pipelines, design analytical data models, contribute backend application code, and help the team adopt modern AI-assisted development practices.
• Write production-quality Python and SQL with the same rigor as any backend engineer, while also being comfortable configuring a Looker explore, building an AWS Glue job, or contributing Java code where needed.
• 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.

Requirements

• 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.
• Deep experience with modern 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) preferred.
• 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).
• Experience in building or contributing to AI/ML features: feature stores, training pipelines, model serving, or RAG architectures.
• Familiarity 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.

Qualifications

• Expert-level proficiency in Python and SQL.
• Hands-on experience with AWS data services, including Glue, S3, Redshift, Athena, CloudFormation, CloudWatch, and IAM.
• Experience with MySQL/Aurora in a production environment.
• Experience with modern BI platforms, particularly Looker (LookML) and Tableau.
• Experience with modern AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, Cody).
• Experience with Java (Spring Boot, Maven/Gradle) and shipping backend services or data-intensive applications to production.
• Experience with AWS certifications (e.g., Solutions Architect, Data Analytics Specialty, or Database Specialty).
• Experience with CI/CD for data assets (dbt CI, Great Expectations, or similar).
• Experience in building or contributing to AI/ML features: feature stores, training pipelines, model serving, or RAG architectures.
• Experience with infrastructure-as-code (Terraform, CloudFormation) and containerized deployments (Docker, ECS/EKS).
• Experience in a startup or high-growth environment where you owned outcomes end to end.
• Experience improving developer experience and productivity through tooling, automation, or process improvements.

Skills

• Python programming
• SQL database management
• AWS data services (Glue, S3, Redshift, Athena, CloudFormation, CloudWatch, IAM)
• Modern BI platforms (Looker, Tableau)
• AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, Cody)
• Java (Spring Boot, Maven/Gradle)
• AWS certifications (Solutions Architect, Data Analytics Specialty, Database Specialty)
• CI/CD for data assets (dbt CI, Great Expectations)
• Experience in health tech, digital health, or regulated industries (HIPAA familiarity)
• Experience with infrastructure-as-code (Terraform, CloudFormation)
• Experience in a startup or high-growth environment where you owned outcomes end to end
• Experience improving developer experience and productivity through tooling, automation, or process improvements

Benefits

Comprehensive benefits package, including health, dental, and vision insurance, along with flexible PTO and work from home options.

Pay

This role offers a base salary of up to $195,000, depending on experience and qualifications.

Schedule

Not specified.