Principal Data Engineer

Company Overview:

Blink Health is the fastest growing healthcare technology company that builds products to make prescriptions accessible and affordable to everybody. Our two primary products – BlinkRx and Quick Save – remove traditional roadblocks within the current prescription supply chain, resulting in better access to critical medications and improved health outcomes for patients.

BlinkRx is the world’s first pharma-to-patient cloud that offers a digital concierge service for patients who are prescribed branded medications. Patients benefit from transparent low prices, free home delivery, and world-class support on this first-of-its-kind centralized platform. With BlinkRx, never again will a patient show up at the pharmacy only to discover that they can’t afford their medication, their doctor needs to fill out a form for them, or the pharmacy doesn’t have the medication in stock.

We are a highly collaborative team of builders and operators who invent new ways of working in an industry that historically has resisted innovation. Join us!

About the Role:

BlinkRx is seeking a highly experienced Principal Data Engineer to design, build, and evolve our core data ecosystem. This role is for a hands-on technical leader who thrives on transforming raw, disparate data into trusted, well-modeled, and analytics-ready assets that power decision-making, AI, and operational systems across the company.

As a senior individual contributor within the Data organization, you will own critical aspects of data architecture, modeling, and transformation. You’ll play a central role in unifying data across domains, evolving schemas and pipelines as the business changes, and ensuring our data foundation supports real-time use cases, advanced analytics, and AI-driven initiatives.

What You Will Do:

Data Architecture & Modeling

• Design and maintain robust data models that clearly define structure, relationships, and business meaning across domains.



• Establish and evolve canonical data definitions, schemas, and dimensional models to support analytics, reporting, and AI use cases.



• Ensure data models balance scalability, performance, and ease of use for downstream consumers.

Data Transformation & Pipelines

• Build and own end-to-end data transformation workflows, from raw ingestion through curated, modeled, and reporting-ready layers .



• Implement scalable ELT/ETL patterns that support batch and real-time data processing.



• Continuously refactor and improve existing pipelines to increase reliability, performance, and clarity as requirements evolve.

Data Integration & Unification

• Integrate data from diverse internal and external sources into a unified, consistent data foundation.



• Resolve data duplication, inconsistency, and fragmentation across systems through thoughtful modeling and transformation.



• Partner with upstream and downstream teams to ensure clean contracts and reliable data interfaces.

AI & Advanced Analytics Enablement

• Design data structures and pipelines that enable AI, machine learning, and advanced analytics use cases.



• Ensure training, feature, and inference data are accurate, timely, and reproducible.



• Collaborate with analytics and data science partners to operationalize AI-ready datasets.

Change Management & Technical Stewardship

• Lead change management for data systems, including schema evolution, backfills, and migration strategies.



• Establish best practices for refactoring data pipelines without disrupting critical reporting or consumers.



• Act as a steward of long-term data quality, maintainability, and technical integrity.

Collaboration & Influence

• Partner closely with Analytics, Product, Finance, Operations, and Engineering to translate business needs into scalable data solutions.



• Communicate complex data concepts clearly to technical and non-technical stakeholders.


• Set standards and provide technical guidance to other data engineers through design reviews and mentorship.

Qualifications:

Minimum Requirements

• 10+ years of experience in data engineering or related software engineering roles.



• Deep expertise in SQL and data transformation frameworks, with strong proficiency in Python.



• Extensive experience designing and maintaining data models (dimensional, relational, and analytical).



• Proven track record of building reliable data pipelines from raw data to analytics and reporting layers.



• Experience integrating and unifying data across multiple systems and domains.



• Strong understanding of data quality, testing, observability, and lifecycle management.



• Excellent communication skills and ability to drive alignment through technical leadership rather than people management.

Preferred Qualifications

• 
  
  
  
  • Experience supporting AI or machine learning workloads with production-grade data pipelines.

  
  
  • Background in healthcare, pharmacy, or other regulated data environments.

  
  
  • Experience with real-time or streaming data architectures.

  
  
  • Familiarity with modern cloud data stacks (e.g., cloud data warehouses, Spark-based processing).
  
  

Why Join Us:

It is rare to have a company that both deeply impacts its customers and is able to provide its services across a massive population. At Blink, we have a huge impact on people when they are most vulnerable: at the intersection of their healthcare and finances. We are also the fastest growing healthcare company in the country and are driving that impact across millions of new patients every year. Our business model not only helps people, but drives economics that allow us to build a generational company. We are a relentlessly learning, constantly curious, and aggressively collaborative cross-functional team dedicated to inventing new ways to improve the lives of our customers.

We are an equal opportunity employer and value diversity of all kinds. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.