Staff Data Engineer

Join9am; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Remote work options

Professional development budget

Health, dental, and vision coverage

Job summary

Join9am is seeking a senior data platform engineer to own the data platform architecture, pipelines, and governance while hands-on building and operating it. The role spans production pipelines, warehouse models, integrations, and support for analytics and ML needs.

You will lead data quality, governance, and incident response, mentor colleagues, and guide responsible use of AI-assisted development tools in a collaborative, fast-moving environment. Remote options available.

Qualifications

• 10+ years in data engineering or related field.
• Expert Python and SQL with production pipeline experience.
• Experience operating cloud data pipelines and a cloud data warehouse (AWS/Redshift).

Responsibilities

• Design, build, and maintain Python ETL/ELT pipelines and data services (AWS Glue, S3, Redshift, Athena).
• Set platform architecture, coding practices, and guide roadmap, performance and cost decisions.
• Develop semantic layers for self-service reporting and optimize SQL and databases.
• Create integrations with internal/external systems and contribute backend code as needed.
• Ensure data quality, governance, monitoring, and incident response including health data considerations.

Skills

Python

SQL

Tools

AWS Glue

AWS Redshift

S3

Athena

CI/CD

Job description

Role overview

Own the data platform behind business reporting and analytics, setting its architecture and technical standards while continuing to build and operate it hands-on. The work spans production pipelines, warehouse models, integrations, data reliability, and support for analytics and machine learning needs.

Responsibilities

• Design, build, and maintain Python-based ETL/ELT pipelines and operate data services including AWS Glue, S3, Redshift, and Athena.
• Set platform architecture, coding practices, and technical direction; evaluate tools and guide roadmap, performance, and cost decisions.
• Develop analytical models and semantic layers for self-service reporting, and write and tune complex SQL and database objects.
• Build integrations with internal and external systems, contributing backend code where needed.
• Own data quality, governance, monitoring, alerting, and incident response, including appropriate handling of sensitive health data.
• Partner with product, clinical operations, finance, engineering, and data science teams; mentor colleagues and guide responsible use of AI-assisted development tools.

Requirements

• 10 or more years in data engineering or a combined data and software engineering role.
• Expert Python and SQL skills, including production pipeline design, query optimization, code review, testing, and CI/CD practices.
• Experience operating cloud data pipelines and a cloud warehouse in production; AWS and Redshift are the primary environment described.
• Knowledge of data modeling, including dimensional schemas, slowly changing dimensions, and event-based models.
• Experience protecting sensitive data through suitable access controls and compliance practices.
• Proven ability to set technical standards, explain trade-offs to varied stakeholders, and use AI development tools with sound judgment about security and correctness.

Nice to have

• Cloud certification or equivalent hands-on experience; work in healthcare or another regulated field.
• Experience with data CI/CD, AI/ML pipelines or features, infrastructure as code, containers, orchestration, BI semantic layers, or startup environments.
• A record of improving developer productivity through tooling, automation, or process changes.

Benefits and work setup

• Remote work options, flexible paid time off, health, dental, and vision coverage, and a professional development budget. The team works across locations, with sites in San Diego and Vienna.