Senior Data Engineer: Scalable Pipelines & Architecture

Omada Health; United States; On-site; USD 171,600 - 214,500; Full time

Benefits offered by this job

Health, dental, vision insurance

Remote first culture

Equity grants

401k retirement plan

Generous PTO

Job summary

Omada Health is seeking a Data Engineer to design, build, and maintain robust data architectures and pipelines. You will ensure data integrity, scalability, and performance while enabling analytics and ML initiatives across the organization.

The role emphasizes collaboration with data scientists and analysts, implementing data quality, and training teammates in data engineering best practices. A strong background in ETL, data modeling, and cloud data platforms is required.

Qualifications

• 5+ years building, maintaining scalable data pipelines.
• 3+ years with Airflow or Python-based data pipelines.
• Experience with OLTP/OLAP data modeling and SQL.
• Experience integrating diverse data sources including APIs and databases.
• Experience with cloud data warehouses (Redshift/Snowflake) and AWS.
• Understanding data governance, PHI/PII security best practices.

Responsibilities

• Design, build, and maintain scalable data architectures and pipelines.
• Develop logical and physical data models for BI and analytics.
• Implement and optimize ETL processes ensuring low latency and high throughput.
• Integrate diverse data sources into a unified data platform.
• Collaborate with data scientists, analysts, and engineers on data needs.
• Maintain documentation of architectures, models, and pipelines.
• Monitor production environments and ensure SLAs are met.

Skills

SQL

Python

Airflow

ETL

Data Modeling

Education

Bachelor’s degree in CS or related

Tools

Redshift

Snowflake

AWS

Kubernetes

Job description

Omada Health is seeking a Data Engineer to design, build, and maintain robust data architectures and pipelines. You will ensure data integrity, scalability, and performance while enabling analytics and ML initiatives across the organization.

The role emphasizes collaboration with data scientists and analysts, implementing data quality, and training teammates in data engineering best practices. A strong background in ETL, data modeling, and cloud data platforms is required.