Sr. Data Engineer

Prolaio • Chicago, IL

8d

About The Position

As a Senior Data Engineer, you will design, build, and operate data pipelines in a regulated environment. You will work closely with data science and clinical teams, which own the medical and research questions, and with the Data Architect on platform standards, data models, and governance. The role supports Prolaio’s technology-enabled precision cardiology platform and its work to improve outcomes for people affected by heart disease and heart risks.

You will build and evolve Prolaio’s data ecosystem, creating batch, streaming, and hybrid pipelines orchestrated with Dagster. You will develop and maintain dbt models in BigQuery across staging, intermediate, and mart layers, and ingest and normalize structured and unstructured sources such as cardiology wearable and device signals, EHR, claims, medication, and patient-reported data. You will contribute to platform architecture and make decisions about storage, compute, partitioning, cost, and APIs.

The role also contributes to data lifecycle controls, traceability, lineage, provenance, reproducibility, auditability, and validated operation in a regulated setting. You will support data scientists and ML workflows, contribute to internal applications and Python libraries, own data-platform CI/CD through GitLab CI, help monitor pipeline health and costs with Datadog, participate in incident response, and mentor engineers while helping establish team standards.

Requirements

• At least 6 years of experience in data engineering.
• Expertise in Python and SQL.
• Experience with GCP, or AWS/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 ML workflows.
• Experience collaborating with data scientists, product teams, and clinical or quality stakeholders.
• Experience with Kubernetes.

Nice To Haves

• Hands-on GCP experience, including IAM, Cloud Storage, Cloud Run, Pub/Sub, and networking.
• Infrastructure as code experience with 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 such as SaMD, FDA, GxP, or HIPAA.
• Experience with streaming tools such as Pub/Sub or Kafka.

Responsibilities

• Design, build, and maintain batch, streaming, and hybrid data pipelines orchestrated with Dagster, covering 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, EHR, 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 lifecycle controls for retention, access control, lineage, provenance, reproducibility, and auditability.
• Use Dagster assets and dbt lineage to trace data from source to output.
• Document pipelines and maintain traceability while working with Quality and Security teams to support validated operation in a regulated setting.
• Back pipeline changes with automated tests and data quality checks.
• Provide data scientists with tools and processes to experiment and iterate efficiently.
• Contribute to ML 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 costs with Datadog, and participate in incident response.
• Help mentor other engineers and set engineering standards for the data team.

Benefits

• Competitive salary, performance bonus, and equity.
• Medical, dental, and vision plans with multiple options and company contributions.
• HSA, FSA, commuter benefits, and a $1,200 annual Lifestyle Spending Account.
• Generous paid time off, sick leave, and company holidays.
• Paid parental leave and caregiver leave, plus support for growing families.
• Company-paid life insurance and short- and long-term disability coverage.
• 401(k) plan.
• Access to telehealth and optional supplemental coverage.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed