Principal Data Engineer , NY

Blink Health is the fastest growing healthcare technology company that builds products to make prescriptions accessible and affordable to everybody. Our two primary products – Blink Rx 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.

Blink Rx 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 Blink Rx, 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!

Blink Rx 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.

• 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.
• 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.

• 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.

• 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.

• 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.
• 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.

• 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…