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Specialized care that’s actually there—every step of the way
Senior Data Engineer
Location
United States
Posted
16 days ago
Salary
$195K / year
Seniority
Senior
Job Description
Senior Data Engineer
9amHealth
• 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.
Job 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.
- Familiarity with AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, Cody) and a demonstrated interest in integrating AI into engineering workflows.
Benefits
- Health, dental, and vision insurance
- Flexible PTO and work from home options
- Professional development budget
- Support for continuing education
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