Data Engineer II- Life Sciences

Location: New York, United States; Workplace: Hybrid

Company

hirify.global provides healthcare information and data products designed to improve doctor interactions, patient outcomes, and the drug development lifecycle.

What you will do

• Build and maintain Python and PySpark pipelines for clinical trial data intake, scoring, and status logic.
• Transform CSV, JSON, Parquet, API, and customer data into hirify.global's internal data models.
• Write and optimize SQL for large datasets, pipeline validation, data investigation, and customer-facing analysis.
• Translate clinical subject-matter expertise into data rules and explain pipeline results to non-engineering stakeholders.
• Implement data quality checks, validation, reconciliation, monitoring, alerting, and dashboards.
• Respond to customer-driven changes while maintaining enterprise SLA reliability and engineering standards.

Requirements

• Production experience building and maintaining data pipelines in Python.
• Hands-on experience with PySpark or a comparable distributed data processing framework.
• Strong SQL skills with large, messy, multi-source datasets.
• Knowledge of testing, code review, documentation, and CI/CD practices.
• Experience collaborating with cross-functional and non-technical stakeholders.
• Ability to work in a hybrid role based in New York.

Nice to have

• Experience with Argo, Airflow, Databricks, dbt, or similar orchestration tools.
• Clinical trial, healthcare, regulated-domain, entity matching, or data mastering experience.
• Familiarity with AWS services such as S3, Lambda, or ECS.

Culture & Benefits

• Work in a healthcare data environment focused on health equity and improved patient outcomes.
• Collaborate with clinical subject-matter experts, analysts, customer-facing teams, and engineers.
• Operate in an environment where reliability, data quality, and on-time delivery are central priorities.
• Inclusive workplace with equal employment opportunity and reasonable accommodation support.