Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Мало
$115к-192к/год
$140к$160кмедиана$190к
По похожим ролям (49) ~ $160к/год
На СНГ рынке: $4к/мес ($3к - $5.9к)
73
Хорошая вакансия
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Это четко описанная senior-роль в крупной медицинской компании с современным стеком и хорошими льготами, но зарплата ниже рыночной медианы, а широкий диапазон не дает понять, на какую сумму можно рассчитывать.
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Ниже рынкаСовременный стекПонятная рольМедицинские данныеХороший пакет льгот
Оценка от Hirify AI
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Data Ops - Lead Data Builder (Databricks): Building trusted, reusable Silver and Gold data products from architectural designs and business requirements with an accent on Databricks, Spark, dimensional and medallion modeling, and production-grade delivery. Focus on implementing governed CI/CD pipelines, optimizing Spark and SQL transformations, embedding automated data-quality validation, and applying AI and automation without compromising governance, security, or quality.
Location: Remote, United States Work at Home
Annual salary: $115,200–$192,000 USD, depending on experience and geographic location; eligible for an annual bonus plan.
Company
hirify.global provides healthcare and health services through Cigna Healthcare and Evernorth Health Services, focusing on improving the health and vitality of clients, customers, and patients.
What you will do
Build production-ready Silver and Gold data products from Data Architecture designs, business requirements, business rules, and acceptance criteria through MVP.
Develop physical Silver structures using enterprise-agnostic models and reference patterns, then promote them through governed CI/CD pipelines.
Co-design and deliver reusable Gold data products while maintaining common build standards and guardrails across federated ownership.
Capture business context and metadata, refactor learning-stage and bespoke work into durable assets, and prepare solutions for partner-team handoff.
Develop, test, and productionize data solutions while clearing quality, security, and cost checks.
Collaborate with Data Architecture, Data Analysis, Products & Integration, Platform Engineering, IT, DevOps, AI Enablement, data science, analytics, the Hyderabad Data Operations team, and external service partners.
Requirements
7+ years building production-grade data solutions, with demonstrated depth in analytics engineering or equivalent business-plus-build work.
A 50/50 blend of business fluency and hands-on engineering discipline.
Hands-on experience with Databricks, Spark, Unity Catalog, SQL, and Python.
Familiarity with Snowflake and Teradata in addition to a Databricks-first stack.
Expert knowledge of dimensional and medallion Silver/Gold modeling within an enterprise-agnostic data model.
Working knowledge of CI/CD pipelines, automated code evaluation, and controlled production promotion.
Strong software-engineering discipline, including Git, code review, and efficient reusable code.
Experience performance-tuning and cost-optimizing Spark and SQL transformations at scale.
Familiarity with data governance and cataloging tools such as Collibra, plus automated data-quality testing and validation in every solution.
Ability to learn new data domains quickly, translate business logic into reusable data products, and apply AI and automation while preserving quality and governance.
Nice to have
Experience in complex, regulated enterprises.
Healthcare or PBM data experience.
Culture & Benefits
Remote work from a United States home location; home internet must use cable broadband or fiber with at least 10 Mbps download and 5 Mbps upload.
Medical, vision, dental, well-being, and behavioral health benefits available from the first day of employment.
401(k), company-paid life insurance, tuition reimbursement, at least 18 days of paid time off annually, paid holidays, and leaves of absence.
Work is performed as an individual contributor within a global delivery model, partnering across architecture, engineering, analytics, and operations teams.
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