pythonsqlapisscalasparkpysparkdata pipelinescloud infrastructuremaster data managemententity resolution
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата не указанаОчное собеседованиеАктуальный стекПонятная рольМедицинские данные
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Staff Software Engineer (Health Plans): Building large-scale data pipelines, entity matching services, APIs, and self-service tools that improve healthcare provider directory accuracy with an accent on PySpark, Scala, SQL, master data management, and messy enterprise data. Focus on designing scalable data processing systems, integrating clinical and provider data, improving reliability and observability, and turning complex data into customer-facing products.
Location: New York; hybrid workplace. An in-person final interview is required and may require travel depending on candidate location.
Company
hirify.global provides healthcare information and data products designed to improve doctor interactions, health equity, medical insights, and drug development.
What you will do
Design, build, and operate large-scale data pipelines for ingesting, transforming, matching, and syncing client data with PySpark, Scala, and SQL.
Build and improve entity matching services, schemas, data asset management features, scoring, status assignment, and configurable intake.
Develop APIs, backend services, customer-facing applications, and self-service internal tools for exploring and working with data.
Debug messy enterprise client data end to end, improve ingestion reliability, and integrate clinical and provider data for new products and customers.
Improve pipeline performance, reliability, observability, testing, and documentation while contributing to architecture decisions, design reviews, and code reviews.
Partner with product, design, and adjacent engineering teams to shape and ship customer-focused features.
Requirements
Deep experience designing, building, and running production big data pipelines at scale, including ETL/ELT, orchestration, scheduling, and monitoring.
Strong proficiency in PySpark, Scala, Python, and SQL.
Solid experience with distributed data processing and Spark performance tuning.
Experience building APIs or backend services supporting customer-facing applications.
Working knowledge of cloud infrastructure such as AWS, GCP, or Azure.
Hands-on experience with entity resolution, record matching, or master data management, plus data quality, scoring, or validation frameworks.
Comfort working directly with messy client source files and onboarding enterprise customers.
Product-engineering mindset with attention to how customers use built products.
Nice to have
Full-stack experience or experience building web UIs with a modern framework such as React.
Experience building products that turn complex data into customer-facing features.
Experience building internal self-service tools.
Experience with healthcare data, including provider or HCP directories, rosters, credentialing, clinical trial, or site feasibility data.
Experience with CTMS or other clinical systems data.
Culture & Benefits
Inclusive workplace committed to equal opportunity and diversity.
Reasonable accommodations are available for applicants with disabilities.
Final interviews are conducted in person.
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