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Prolaio

Decentralized cardiovascular trials with wearables

Data Engineer in Test

Performance Testing +1Confirmed live in the last 24 hours
Full-timeChicago, IL, USAIn-person

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Science, or a related field.
  • At least 3 years of software testing experience, specifically focused on data pipelines, data lakes, and data warehouses.
  • Strong understanding of data engineering concepts and technologies, including ETL/ELT processes, data lakes, and cloud-based data warehouses.
  • Proficiency in SQL and Python for data querying, analysis, and test automation.
  • Experience working with cloud-based data platforms, particularly Google Cloud Platform and BigQuery.
  • Demonstrated experience generating synthetic data for testing, including designing datasets that realistically represent production data characteristics.
  • Familiarity with data testing tools and frameworks such as pytest, unittest, or TestNG.
  • Strong knowledge of time-series data processing, analysis techniques, and best practices.

Responsibilities

  • Develop and execute comprehensive test plans, test cases, and automated test suites for data pipelines to ensure data quality, consistency, and system performance.
  • Test and validate ETL/ELT processes and data workflows across data lake environments, confirming the accuracy of data transformations and adherence to business logic.
  • Validate data ingestion, processing, and storage within scalable cloud data platforms such as BigQuery, ensuring computed data correctly reflects raw time-series biosensor inputs.
  • Design, build, and maintain synthetic data generation tools and datasets that mimic real-world time-series biosensor data, enabling thorough test coverage where real patient data is limited or restricted.
  • Collaborate with data engineers and data scientists to define testing requirements and ensure data accuracy throughout the data lifecycle.
  • Conduct performance testing and benchmarking on data systems to evaluate scalability under high data loads and identify performance bottlenecks.
  • Monitor and report on key performance metrics, identifying potential data anomalies, inconsistencies, or performance issues.
  • Contribute to the continuous improvement of testing processes, automation frameworks, and tools used across data workflows.

Desired Qualifications

  • Certifications in data engineering or cloud platforms, such as GCP Certified Data Engineer or Databricks Certified Data Engineer.
  • Experience in a regulated industry such as healthcare, MedTech, or BioTech, with familiarity with data governance and regulatory compliance frameworks.
  • Prior experience testing systems subject to IEC 62304 or similar SaMD quality standards.

About the Company

Prolaio

Decentralized cardiovascular trials with wearables

Prolaio builds cardiovascular clinical research infrastructure that turns homes into trial sites using medical-grade wearables to capture continuous real-world heart data. Its intelligence engine converts these signals into clinically robust endpoints and FDA-cleared digital biomarkers, supporting recruitment, 24/7 data capture, adaptive analytics, and trial dashboards. The platform enables fully managed real-world trials as well as digital enablement of existing protocols and post-discharge monitoring, with dozens of validated algorithms including FDA-cleared measures across 20+ countries. The goal is to make cardiovascular trials faster, more scalable, and more accurate by using home-based data and standardized digital endpoints.

Company size
51-200
Company stage
Early VC
Total funding
$25.5M
Headquarters
Chicago, IL
Founded
2022

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