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Omada Health

Staff Software Engineer, Data Products

Omada Health
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about 14 hours ago
Remote, United StatesStaff+
H1B Sponsor

Base Salary

$176k - $253k/yr

Responsibilities

  • Design, build, and maintain reusable feature datasets for machine learning use cases.
  • Establish self-service foundations for dataset creation across the organization.
  • Partner with Data Scientists to create production-ready feature pipelines.
  • Identify source data and transformations for feature engineering.
  • Balance features freshness, correctness, latency, and computational efficiency.
  • Build datasets for historical model training and production inference.
  • Design and implement batch and streaming data pipelines.
  • Optimize large-scale distributed processing for performance and cost.
  • Ensure data quality through testing and monitoring.
  • Lead architecture discussions for large-scale ML data systems.

Requirements

  • 8+ years of experience in building large-scale production data platforms.
  • Experience designing reusable datasets for machine learning.
  • Demonstrated experience collaborating with Data Scientists.
  • Strong experience with cloud-native data platforms like AWS.
  • Proficient in SQL and programming languages such as Python, Java, or Scala.
  • Experience with Apache Spark and data orchestration platforms.
  • Familiarity with feature stores and ML data lifecycle concepts.
  • Experience with healthcare or large-scale event data is a plus.

Benefits

  • Competitive salary with generous annual cash bonus.
  • Equity grants.
  • Remote first work from home culture.
  • Flexible Time Off for rest and personal connections.
  • Generous parental leave.
  • Health, dental, and vision insurance with above-market contributions.
  • 401k retirement savings plan.
  • Lifestyle Spending Account (LSA).
  • Mental Health Support Solutions.

Tech Stack

Amazon RedshiftApache AirflowApache FlinkApache KafkaApache SparkAWSDatabricksDatadogDockerKubernetesPostgreSQLPythonRuby on RailsSnowflakeSQL

Categories

AI & MLData Engineering