Job Description

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.

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