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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