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Prolaio

Decentralized cardiovascular trials with wearables

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeChicago, IL, USAIn-person

About the Job

Requirements

  • At least 6 years of data engineering experience.
  • Expert proficiency in Python and SQL.
  • Experience with GCP, AWS, or Azure.
  • Production experience with dbt, including modeling, testing, macros, and incremental models.
  • Experience with BigQuery or a comparable cloud data warehouse such as Databricks or Redshift.
  • Experience with Dagster or a comparable orchestrator such as Airflow or Prefect.
  • Experience with Docker and large-scale data processing.
  • Experience with structured, semi-structured, and unstructured data, including time-series data.
  • Understanding of MLOps concepts and production machine learning workflows.
  • Experience collaborating with data scientists, product teams, and clinical or quality stakeholders.
  • Experience with Kubernetes.

Responsibilities

  • Design, build, and maintain batch, streaming, and hybrid pipelines orchestrated with Dagster for data ingestion, validation, transformation, enrichment, and publishing.
  • Develop and maintain dbt models in BigQuery across staging, intermediate, and mart layers, with tests, documentation, and clear ownership.
  • Ingest and normalize heterogeneous structured and unstructured sources, including cardiology wearables and device signals, electronic health records, claims, medication, and patient-reported data.
  • Make decisions about storage, compute, partitioning, cost, and APIs, and contribute to target-state architecture and reference patterns.
  • Contribute data lifecycle controls to pipelines, including retention, access control, lineage, provenance, reproducibility, and auditability.
  • Use Dagster assets and dbt lineage to trace data from source to output.
  • Support validated operation in a regulated setting by documenting pipelines, maintaining traceability, and working with Quality and Security teams.
  • Back pipeline changes with automated tests and data quality checks.
  • Enable data scientists to experiment and iterate efficiently through tools and processes.
  • Contribute to machine learning workflows for feature generation, training, deployment, and monitoring.
  • Contribute to internal applications and Python libraries.
  • Own CI/CD for the data platform using GitLab CI, including dbt and Dagster deployments.
  • Help monitor pipeline health, performance, and BigQuery cost with Datadog, and participate in incident response.
  • Help mentor other engineers and set engineering standards for the data team.

Desired Qualifications

  • Hands-on GCP experience with IAM, Cloud Storage, Cloud Run, Pub/Sub, and networking.
  • Experience with infrastructure as code using Terraform.
  • Experience with Datadog.
  • Experience with metadata, lineage, and catalog tools, as well as retrieval or vector tooling for AI use cases.
  • Experience with Databricks.
  • Experience working with healthcare, life sciences, medtech, or other patient data.
  • Experience in regulated or validated environments, including SaMD, FDA, GxP, or HIPAA.
  • Experience with streaming tools such as Pub/Sub or Kafka.

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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