Data Engineer

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Company Overview

A healthcare technology company is focused on bringing high-quality healthcare to patients through advanced technology and data-driven solutions. Its platform analyzes comprehensive patient medical records to identify diagnoses that may otherwise be missed, supporting healthcare providers during point-of-care chart review and population-wide screening.

The organization works with leading health systems to improve healthcare delivery through technology, research, and data. Its engineering teams operate an engineering-first technology environment focused on transparent, code-driven systems and reliable infrastructure.

The organization is seeking a Data Engineer to build and maintain the data pipelines and infrastructure that transform raw data into metrics and insights supporting product decisions and research initiatives.

The role will work closely with Engineering, Product, and Research teams to develop data pipelines, improve data models, support analytics initiatives, and ensure the quality and availability of critical datasets. The position provides opportunities to work across the data stack while developing expertise in distributed data processing, data modeling, and platform operations.

Responsibilities

• Build and maintain data pipelines supporting analytics and research initiatives.
• Develop and improve data models and transformations that reliably deliver data to downstream consumers.
• Partner with engineering teams to identify and resolve data quality issues and help ensure datasets are accurate and trustworthy.
• Support the operation, monitoring, and maintenance of the data platform and its pipelines.
• Collaborate with Product, Engineering, and Research teams to deliver data and insights that inform business and product decisions.
• Investigate pipeline failures, data inconsistencies, and upstream changes while contributing to timely resolution and continuous improvement.
• Optimize data processing workloads and storage patterns to improve performance, scalability, and cost efficiency.
• Contribute to the continued growth, reliability, and operational maturity of the data platform.
• Participate in on-call operational support for owned systems.

Technology Stack

• Amazon S3
• Apache Iceberg
• Amazon EMR
• PySpark
• Dagster
• Kubernetes
• ClickHouse
• PostgreSQL
• FastAPI
• Metabase

Minimum Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, a related field, or equivalent practical experience.
• 3+ years of experience in a data engineering role.
• Experience building and maintaining data pipelines and data models in production environments.
• Proficiency in Python and SQL.
• Experience working with distributed data processing frameworks such as PySpark.
• Experience with cloud-based data platforms and services, preferably AWS.
• Practical experience with LLM-assisted development and an understanding of its capabilities and limitations.
• Willingness to participate in on-call operational support for owned systems.

Preferred Qualifications

• Experience with one or more of the following technologies: Apache Iceberg, AWS Athena, Dagster, ClickHouse, PostgreSQL, FastAPI, or Metabase.
• Experience supporting data quality, monitoring, and observability initiatives.
• Familiarity with healthcare data, including HIPAA compliance, de-identification, or healthcare data standards such as OMOP CDM.
• Experience building or supporting data pipelines used for production workflows.
• Experience working with cross-functional teams in a fast-paced startup environment.

Compensation

The expected base salary range for this position is $160,000 to $190,000, with equity also offered. Compensation may vary based on factors including skills, qualifications, location, and experience, and the range may be modified in the future.

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