Data Engineer

TL;DR

Data Engineer (Python/SQL): Build and maintain data pipelines and infrastructure that turn raw data into metrics and insights for product decisions and research with an accent on distributed data processing, data modeling, and platform operations. Focus on designing reliable transformations, ensuring data quality, and resolving pipeline failures to keep critical datasets accurate and available.

Location: New York City, Los Angeles, or San Francisco metro areas (US work authorization required); Hybrid work with office presence Tuesdays and Thursdays and more frequent in-office time during onboarding and team onsite weeks up to once per month. Relocation assistance available for candidates not residing in the NYC metro area.

Salary: $140,000–$175,000 base + equity

Company

hirify.global is an AI-powered Proactive Documentation platform for healthcare, reviewing EHR patient data to recommend diagnoses and surface clinical evidence.

What you will do

• Build and maintain data pipelines supporting analytics, machine learning development, and research initiatives.
• Develop and improve data models and transformations that deliver reliable data to downstream consumers.
• Partner with engineering teams to identify and resolve data quality issues and ensure datasets are accurate and trustworthy.
• Operate, monitor, and maintain the data platform and its pipelines, including investigating failures and upstream changes.
• Collaborate with Product, Engineering, and Research teams to deliver data and insights for business and product decisions.
• Optimize data processing workloads and storage patterns to improve performance, scalability, and cost efficiency.

Requirements

• US work authorization without visa sponsorship.
• 3+ years of experience in a data engineering role.
• Proficiency in Python and SQL.
• Experience building and maintaining production data pipelines and data models.
• Experience with distributed data processing frameworks such as PySpark.
• Willingness to participate in on-call operational support for owned systems.

Nice to have

• Experience with Apache Iceberg, AWS Athena, Dagster, Clickhouse, PostgreSQL, FastAPI, or Metabase.
• Experience with data quality, monitoring, and observability initiatives.
• Familiarity with healthcare data and standards (e.g., HIPAA, de-identification, OMOP CDM).
• Experience with ML training/evaluation/production pipeline workflows.
• Experience working in a fast-paced startup environment.

Culture & Benefits

• Hybrid schedule with office presence on Tuesdays and Thursdays, plus additional in-office time during onboarding and team onsite weeks.
• 99% employer-paid health benefits (Medical, Dental, Vision) + One Medical subscription.
• 18 PTO days per year + 1 week holiday break; monthly health & wellness budget.
• Equity eligibility; company-sponsored team retreat and social events; sabbatical program.
• Hybrid employees can work from locations outside their home office for up to 6 weeks per year.

Hiring process

• Complete a background check as part of the hiring process.