Staff Data Platform Engineer — Remote ML Pipelines

United States Digital Space LLC; United States; Remote; USD 193,600 - 242,000; Full time

Benefits offered by this job

Remote first culture

Equity grants

Generous parental leave

Health, dental, and vision insurance

Job summary

Omada is seeking a Staff Software Engineer, Data Engineering to lead the design and development of the production data platform powering machine learning across Omada. You’ll collaborate with Data Scientists, Applied AI Engineers, Product Engineers, and other Data Engineers to build trusted data foundations for feature engineering, model training, experimentation, and production inference.

You will own the technical design of feature datasets, ingesting raw behavioral, clinical, and operational

Qualifications

• Bachelor's degree in CS or related field.
• 8+ years building large-scale production data platforms.
• Experience partnering with Data Scientists to productionize feature engineering workflows.
• Experience leading cross-team technical initiatives.
• Strong experience with AWS and cloud-native data platforms.

Responsibilities

• Design, build, and maintain reusable feature datasets for ML use cases.
• Establish self-service foundations to democratize dataset creation.
• Translate modeling requirements into production-ready feature pipelines.
• Define shared, reusable feature definitions across models.
• Balance data freshness, correctness, latency, and efficiency.
• Build batch and streaming pipelines for healthcare, behavioral, and operational data.

Skills

SQL

Python

Java

Scala

Spark

Airflow

Databricks

Kubernetes

Data modeling

NoSQL

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Iceberg

Spark

Redshift

Snowflake

Job description

Omada is seeking a Staff Software Engineer, Data Engineering to lead the design and development of the production data platform powering machine learning across Omada. You’ll collaborate with Data Scientists, Applied AI Engineers, Product Engineers, and other Data Engineers to build trusted data foundations for feature engineering, model training, experimentation, and production inference.

You will own the technical design of feature datasets, ingesting raw behavioral, clinical, and operational