Senior Data Engineer II

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

Blink Engineering strives to build trusted, highly observable, data-driven and AI-enabled products that bring affordable, accessible healthcare to all Americans. Healthcare is one of the most complex systems most of us will ever work in, and high-quality, well-governed data is foundational to both analytics and AI systems that make that complexity understandable, reliable, and scalable.

We are seeking a Staff Data Engineer to own and drive the evolution of Blink’s data engineering function with an AI-first mindset . This role is responsible for shaping and executing a forward-looking data strategy that ensures our data warehouse, pipelines, and analytics foundations are not only correct and reliable, but designed to power machine learning, AI-driven insights, and intelligent automation at scale .

As a Staff engineer, you are a technical leader and force multiplier—deeply hands-on while setting standards, direction, and best practices that scale across teams. You will operate with a high degree of autonomy, proactively identifying risks and opportunities, and influencing how Blink builds, uses, and trusts its data as a strategic asset for both human and AI decision-making .

What You Will Do

• 
  

  Own the technical direction for Blink’s data engineering architecture, balancing immediate business needs with long-term scalability, reliability, maintainability, and AI readiness



• 
  

  Design, build, and evolve core data pipelines, models, and warehouses that support analytics, reporting, operational decision-making, and AI/ML use cases



• 
  

  Proactively assess production data warehouse trends and operational issues, identifying systemic problems and driving durable short- and long-term solutions that improve data quality, freshness, and usability for AI systems



• 
  

  Define and enforce standards for data modeling, data quality, observability, and performance across the data ecosystem, with an emphasis on producing trusted inputs for machine learning and AI



• 
  

  Lead the design and refactoring of large enterprise data warehouses and associated ETLs, simplifying architecture through automation, improved patterns, and AI-friendly data abstractions



• 
  

  Serve as a technical authority in peer code reviews and architecture reviews, setting a high bar for clean, correct, maintainable, and AI-compatible data systems



• 
  

  Partner closely with analytics, product, and engineering teams to translate ambiguous business needs into scalable data solutions, including data products that enable AI-powered features



• 
  

  Identify opportunities to increase leverage through shared frameworks, tooling, reusable data assets, and data products that accelerate AI development



• 
  

  Mentor and guide other data engineers, raising the overall technical maturity and effectiveness of the team in building data systems that safely support AI

Technical Skills

• 
  

  8+ years of experience in data or software engineering, including ownership of production-grade data systems



• 
  

  Strong foundation in data engineering principles, including dimensional modeling, incremental data ingestion, and distributed data processing, with an understanding of how these choices impact AI and ML workflows



• 
  

  Extensive experience building and maintaining robust, scalable ETL pipelines using SQL, Python, Databricks, Spark, and DBT



• 
  

  Advanced SQL skills, including writing and optimizing complex queries across large and diverse datasets



• 
  

  Experience designing, operating, and maintaining columnar data warehouses with a focus on reliability, performance, and suitability for advanced analytics and AI



• 
  

  Hands-on experience with batch and streaming data systems, including Airflow, Databricks / Spark, and relational databases such as Postgres



• 
  

  Experience integrating data platforms with business intelligence tools (e.g., Tableau, QuickSight) and supporting downstream AI and ML consumption



• 
  

  Familiarity with modern infrastructure and DevOps practices, including infrastructure as code (Terraform), containerization, and orchestration (Docker, Kubernetes)



• 
  

  Demonstrated ability to continuously improve data systems through automation, simplification, and thoughtful architectural change, especially in service of scalable AI-driven capabilities

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.