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Tebra

Builds software for independent medical practices

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USARemote

About the Job

Requirements

  • At least 3 years of professional experience in Data Engineering, Software Engineering, or a related field.
  • At least 2 years of hands-on experience building and maintaining production data pipelines supporting analytics, reporting, or machine learning workloads.
  • Strong proficiency in Python and SQL, with experience developing production-quality data pipelines.
  • Experience with modern data processing technologies such as Spark, Airflow, Kafka, or similar distributed data platforms.
  • Experience working with cloud-based data platforms such as Databricks, Snowflake, Delta Lake, or equivalent lakehouse technologies.
  • Understanding of data modeling, data warehousing, and data governance best practices.
  • Familiarity with machine learning data workflows, including training datasets, feature engineering, and data quality concepts.
  • Experience deploying and supporting production data pipelines with monitoring, testing, and continuous integration and continuous delivery practices.
  • Ability to collaborate effectively across engineering and product teams.

Responsibilities

  • Design, build, and maintain scalable data pipelines for feature extraction, training data generation, and model monitoring.
  • Develop and enhance data systems that support analytics and machine learning workloads, including data lakehouse and feature store technologies.
  • Monitor production data pipelines, identify data quality issues or pipeline failures, and implement improvements to ensure reliability and freshness.
  • Participate in engineering design discussions and contribute to technical decisions around data architecture and pipeline implementation.
  • Build reusable data engineering components, including automated data quality checks, schema validation, and testing frameworks.
  • Translate business requirements into scalable data solutions that enable analytics and machine learning use cases.
  • Optimize SQL queries, Spark workloads, and data processing pipelines to improve performance and scalability.
  • Collaborate with Machine Learning Engineers and cross-functional partners to support MLOps best practices, including data versioning, lineage, and reproducibility.
  • Break down technical work into manageable tasks and deliver high-quality solutions within an agile team.

About the Company

Tebra

Builds software for independent medical practices

Tebra builds cloud software for independent medical practices and the billing companies that support them, connecting clinical care with everyday practice administration. Its EHR+ platform brings patient records, insurance claims and practice marketing into one system, so practices manage clinical and business tasks through connected tools. Clinicians use it to order prescriptions and lab tests, while office teams coordinate patient appointments and collect payments. Practices pay subscriptions based on prescribing providers, with access for nonclinical staff included. Tebra was formed in 2021 through the merger of Kareo and PatientPop and is headquartered in Corona del Mar, California.

Company size
1,001-5,000
Company stage
Early VC
Total funding
$387M
Headquarters
Newport Beach, CA
Founded
2021

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