Senior Data Engineer

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

📋 Description

• Design, construct, and sustain scalable data pipelines and ETL/ELT workflows using Python with AWS Glue, Apache Spark, Airflow, or similar orchestration tools.

• Develop production-level Python code for DWH logic, reporting tasks, data transformations, and internal tools, adhering to software engineering best practices (testing, code review, CI/CD).

• Create and enhance analytical data models (dimensional, OBT, or hybrid) that support self-service BI and advanced analytics applications.

• Design and manage dashboards, explores, and semantic layers in Looker and/or Tableau; act as the analytics infrastructure owner, ensuring data quality and governance.

• Contribute backend application code in Java (Spring Boot) or Python to facilitate data-heavy features, API integrations, and internal services.

• Advocate for modern AI coding practices within the data team, utilizing tools such as GitHub Copilot, Claude, Cursor, or other AI-assisted development environments to improve delivery speed and code quality.

• Create and maintain detailed SQL assets (stored procedures, views, complex queries) across Redshift, Aurora/MySQL, and Athena.

• Operate and refine AWS data infrastructure, including Glue, S3, Redshift, CloudFormation, CloudWatch, IAM, and Athena.

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

• Implement frameworks for data quality, monitoring, alerting, and incident response processes for the data platform.

• Contribute to the architecture and data strategy for AI/ML features, including data preparation, feature engineering, and model monitoring.

• Mentor current data analysts and data engineers; assist in establishing team standards, code review practices, and documentation norms.

⛳️ Requirements

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

• Strong foundation in software engineering: this role necessitates someone capable of writing, testing, debugging, and deploying production code, not merely querying data.

• Expert-level proficiency in Python: extensive experience in building production data pipelines, ETL processes, and reporting systems in Python.

• Expert-level SQL skills: familiarity with window functions, CTEs, recursive queries, query optimization, and performance tuning at scale.

• Practical experience with AWS data services, particularly Glue, S3, Redshift, Athena, CloudFormation, CloudWatch, and IAM.

• Experience with MySQL/Aurora in a production context.

• Hands-on experience in constructing and managing data pipelines using AWS Glue, Spark, dbt, Airflow, or equivalent frameworks.

• Extensive experience with at least one modern BI platform. Looker (LookML) is strongly preferred; Tableau is also valued. This should encompass semantic modeling, dashboard development, and self-service enablement.

• Strong 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 in deploying 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 (familiarity with HIPAA is an advantage).

• 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).

• Previous experience in a startup or high-growth environment where you were responsible for outcomes end to end.

• Proven track record of enhancing developer experience and productivity through tooling, automation, or process improvements.

🏝️ Benefits

• Health insurance

• Dental insurance

• Vision insurance

• Flexible PTO

• Work from home options

• Professional development budget

• Support for continuing education