Senior Data Engineer II

Blink Health • New York, NY

5h

About The Position

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.

Requirements

• 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

Responsibilities

• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed