Senior Software Engineer, Data Engineering
Omada Health
- Remote
- Remote
- Posted Aug 14, 2026
Job description
About the role
Senior Software Engineer – Data Engineer responsible for designing, building and maintaining scalable data architectures, models and pipelines, ensuring data quality, performance and governance while collaborating with data scientists, analysts and product teams.
About the company
Omada Health is a virtual‑first digital health company that uses human‑led care teams, connected devices and AI‑enabled technology to deliver personalized, data‑driven care for chronic diseases, serving over two million members across employers, health plans and health systems.
Requirements
- 5+ years building, maintaining and orchestrating scalable data pipelines.
- 3+ years developing data integration using Airflow or Python‑based pipeline codebases.
- Experience with integration patterns, backend software development and distributed computing.
- Proven ability to improve ETL performance and write efficient SQL queries.
- Data modeling experience for OLTP and OLAP applications.
- Hands‑on experience with AWS cloud services.
- Familiarity with workflow management tools (Airflow preferred) and cloud data warehouses (Redshift preferred).
- Strong problem‑solving and analytical skills; experience handling PHI/PII and security best practices.
- Proficiency in SQL and relational databases (MySQL, PostgreSQL) and analytical SQL on MPP databases (Redshift, BigQuery, Snowflake).
- Proficiency in Python and/or Java or Scala.
- Knowledge of data modeling techniques (3NF) and tools (ER/Studio, ERwin).
- Software engineering mindset with best practices, automated testing and maintainable code.
- Experience with big data technologies (Lambda, Iceberg/Delta Lake, Spark, Kafka) and BI tools.
- Excellent written and verbal communication skills for cross‑functional collaboration.
- Ability to lead projects with minimal guidance and drive quality software.
- Bachelor’s degree in Computer Science or related field preferred.
- Bonus: experience with NoSQL databases, building internal frameworks or productivity tools, and using generative AI to improve workflows.