Data Engineer

Headquarters: United States - Remote

Tebra only initiates contact with candidates via email from an official Tebra email address (@ tebra.com , @ patientpop.com , or @ kareo.com ) or through our applicant tracking system, Greenhouse. We will only ask you to provide sensitive personal information through our official application portal — not via social media or text message. We do not conduct interviews via instant messaging.

About the Role

As a Data Engineer focused on AI/ML , you’ll build, maintain, and optimize the data infrastructure that powers Tebra’s intelligent features. You’ll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to transform complex healthcare data into high-quality datasets and real-time features that enable machine learning models.

This is a hands-on engineering role where you’ll contribute to scalable data pipelines, improve data quality, and help ensure our AI systems are powered by reliable, performant, and well-governed data. You’ll work on modern data platforms and gain experience building solutions that support both model training and production inference.

Your Area of Focus

• 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 ML 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.

Your Professional Qualifications

• 3+ years of professional experience in Data Engineering, Software Engineering, or a related field.

• 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 CI/CD practices.

• Strong problem-solving skills, attention to detail, and the ability to collaborate effectively across engineering and product teams.

• Excellent communication skills and a desire to continuously learn new technologies and engineering practices.

#LI-SS1 #LI-Remote
We are dedicated to attracting and retaining top talent with competitive and fair compensation. For this position, this range reflects our Zone 1 (National Average) pay band. Your specific compensation is thoughtfully determined by your experience, qualifications, the specific requirements of the role, and your Geo Zone. Our geo-zone system ensures your pay is competitive for your location, recognizing varying costs of labor across regions.

Our four geo zones are designed to reflect this:
Zone 1: National Average
Zone 2: Moderately Higher Cost Regions
Zone 3: High-Cost Regions
Zone 4: Lower-Cost Regions

Beyond base compensation, Tebra offers eligible employees the opportunity for variable pay and a robust benefits package, reflecting our commitment to your overall well-being. In compliance with California pay transparency laws, the specific compensation range applicable to your Geo Zone will be shared during your initial talent screen.

Zone 1 (National Average)
$128,000 — $145,200 USD

About Tebra

Tebra is the only all-in-one EHR+ platform built exclusively for independent healthcare practices. Designed to replace the clunky, fragmented tools built for corporate systems, Tebra connects EHR software, billing, automation, telehealth solution, and marketing — so providers can spend less time on admin and more time with patients. More than 42,000 private practices trust Tebra to streamline operations, increase revenue, and reduce burnout — helping clinicians leave work on time and rediscover their purpose. Learn more at www.tebra.com .

Our Values

Start with the Customer

We get to know our customers - and their patients - and look at the world through their lens.

Keep It Simple

Healthcare is too complex. We aim to simplify it for everyone.

Stay Entrepreneurial

We reject the status quo and solve problems with creativity, perseverance, and a bias to action.

Better Together

We are diverse, humble, and collaborative. We put the team first and win together.

Celebrate Success

Life is short and joy is underrated. We take time to have fun and celebrate success.

Perks & Benefits…

Source: We Work Remotely (https://weworkremotely.com/remote-jobs/tebra-data-engineer)