Staff Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Report directly to the VP of Data.

• Take ownership of the data platform that addresses the current and future data needs of the business.

• Define and manage the architecture, technical standards, and coding practices for the data platform.

• Assess and suggest data technologies while contributing to the platform roadmap.

• Enhance platform performance and manage costs effectively.

• Design, implement, and maintain scalable ETL/ELT pipelines in Python utilizing AWS Glue.

• Lead the development of analytical data models and the semantic layer for self-service BI and advanced analytics.

• Create integrations between the data platform and both internal and third-party systems.

• Contribute backend code as required.

• Establish technical standards for AI-assisted development practices across the data team.

• Write, optimize, and maintain complex SQL and database objects in Redshift.

• Manage and optimize AWS data infrastructure, including Glue, S3, Redshift, and Athena.

• Ensure data quality, governance, and platform reliability, which includes monitoring, alerting, and incident response.

• Facilitate AI/ML initiatives through data preparation, feature engineering, and model monitoring.

• Elevate team technical standards through code reviews, architectural decisions, and active mentorship.

• Collaborate with clinical operations, product, finance, and engineering teams to convert ambiguous business inquiries into reliable, documented data products.

⛳️ Requirements

• 10+ years of professional experience in data engineering or a combined data/software engineering role.

• Strong background in data or software engineering, including the capability to write, test, debug, and deploy production code independently.

• Familiarity with code review and CI/CD practices.

• Expert-level proficiency in Python.

• Expert-level SQL knowledge, including window functions, CTEs, recursive queries, and query optimization at scale.

• Practical experience with cloud data services, preferably AWS.

• Experience in building and managing production data pipelines on cloud data services.

• Proven experience with a cloud data warehouse, ideally Amazon Redshift.

• Skills in schema design and performance tuning.

• Experience managing sensitive data such as PHI, with appropriate access controls and compliance practices.

• Understanding of star/snowflake schemas, slowly changing dimensions, and event-based models.

• Experience in setting technical direction and standards.

• Professional use of AI-assisted development tools with sound judgment regarding correctness, security, and review.

• Ability to communicate technical trade-offs and risks clearly to both technical and non-technical stakeholders, including executives.

• Preferred: professional-level cloud certification or equivalent hands-on experience.

• Preferred: experience in health tech, digital health, or another regulated industry.

• Preferred: experience with CI/CD for data assets, such as dbt CI or Great Expectations.

• Preferred: background in contributing to AI/ML features.

• Preferred: experience with Terraform or CloudFormation, Docker, ECS/EKS.

• Preferred: experience in startup or high-growth environments.

• Preferred: experience enhancing developer experience and productivity.

• Preferred: familiarity with Apache Spark, Airflow, or equivalent technologies.

• Preferred: understanding of BI platforms and semantic layers like Looker/LookML.

• Must have authorization to work in the United States without visa sponsorship.

🏝️ Benefits

• Professional development budget.

• Support for continuing education.

• Health insurance.

• Dental insurance.

• Vision insurance.

• Flexible PTO.

• Options to work from home.

• Collaborative learning environment.

• Opportunity to make a significant impact on chronic disease management and patient outcomes.