About the job
Role Overview

We’re hiring a Senior Data Engineer to architect and build the secure, compliant, and scalable data infrastructure that powers analytics, reporting, and AI-driven insights across our platform. You will design PHI-aware data pipelines, define data models, and implement governance frameworks that ensure the integrity, accessibility, and confidentiality of sensitive healthcare data. This is a senior-level, hands-on role for someone who thrives on creating data systems that balance compliance, performance, and usability. You’ll collaborate with product, engineering, and compliance teams to enable data-driven decision-making across the organization.

Key Responsibilities

• Design, build, and maintain Postgres data models optimized for analytics, reporting, and scalability.
  
  

• Develop and manage PHI-aware ETL pipelines with strong encryption, masking, and auditability.
  
  

• Implement audit logging and HIPAA-compliant data practices across data flows and storage layers.
  
  

• Build and maintain secure analytics environments with strict access control and governance.
  
  

• Create and manage data catalogs to ensure transparency, discoverability, and compliance.
  
  

• Implement access partitioning and role-based controls for sensitive data domains.
  
  

• Collaborate with engineering and compliance teams to ensure end-to-end data protection.
  
  

• Build dashboards and reporting pipelines that deliver real-time insights to stakeholders.
  
  

• Automate data workflows and promote best practices for data reliability, lineage, and observability.
  
  

• Partner with cross-functional teams to align data architecture with business and product goals.
  
  

Qualifications

Required:

• 5+ years of experience in data engineering or related backend roles.
  
  

• Strong proficiency in Postgres with expertise in data modeling, indexing, and query optimization.
  
  

• Hands-on experience designing and managing PHI-aware ETL pipelines.
  
  

• Strong understanding of HIPAA compliance, audit logging, and secure analytics principles.
  
  

• Proven experience building data catalogs, implementing access partitioning, and enforcing data governance.
  
  

• Experience developing dashboards and reporting systems to visualize key metrics.
  
  

• Ability to collaborate with compliance, security, and engineering teams to ensure data trust and transparency.
  
  

• Deep commitment to data integrity, scalability, and reliability in production systems.
  
  

Preferred:

• Experience with DBT for data transformation and modeling.
  
  

• Familiarity with BigQuery for scalable analytics and warehousing.
  
  

• Experience using Airflow for orchestration and workflow automation.