Director Analytics Infrastructure, Pipeline Operations
工作标题:分析基础设施总监,管道运营职位:远程位置 (美国),远程,美国工作地点类型:远程工作合同类型:全日制工作资深级别:工作身份证 REQ-10074007 Jul 28, 2026 USA 可用在:英语摘要远程诺瓦蒂斯有令人兴奋的机会为一个主任,分析基础设施和管道运行。这个角色负责建设下一代,人工智能驱动自动数据管道和可扩展的数据存储库,使企业数据科学和规模分析成为可能。通过利用先进的人工智能技术,现代数据工程工具和功能工程平台,该董事创建了自助服务,分析准备的数据集和企业特性商店,使专家数据科学家和公民数据科学家能够快速开发,部署和扩展模型。此职位可以远程建立在美国任何地方 (根据法律实体可能存在一些限制).请注意,这一角色不会提供迁移。工作时间和旅行 (国内或国际)的预期将由招聘经理定义。本职位需要20%的旅行。关于角色关键责任 · 设计和实施智能,自治数据管道,利用 AI/ML 进行自动化数据质量监测,异常检测和修复。· 建立并维护实现多种模型和使用情况中重用功能的集中化特征存储器。·创建针对数据科学/人工智能工作流程优化的策划数据库,包括培训数据集,评估数据集和生产服务层。·开发自动化特征工程管道,将原始数据转换为分析准备的特性,以后续谱列。·与 IT 合作,优化高性能数据科学工作的分析平台架构。· 建立自动化管道,集成包括销售,CRM,患者索赔,现实证据和非结构数据等多种数据来源。· 创建自助服务的数据访问层,使数据科学家和分析师能够独立查询和提取数据。· 为数据可用性,新鲜度和质量制定 SLA;实施监测和可观察性的解决方案。
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Job Title: Director Analytics Infrastructure, Pipeline Operations
Job Location: Remote Position (USA), Remote, US
Job Location Type: Remote
Job Contract Type: Full-time
Job Seniority Level:
Job ID REQ-10074007
Jul 28, 2026
USA
Available in: English
Summary
Remote
Novartis has an exciting opportunity for a Director, Analytics Infrastructure & Pipeline Operations. This role is responsible for building next-generation, AI-powered automated data pipelines and scalable data repositories that enable enterprise data science and analytics at scale. By leveraging advanced AI technologies, modern data engineering tools, and feature engineering platforms, this director creates self-service, analytics-ready datasets and enterprise feature stores that empower both expert data scientists and citizen data scientists to rapidly develop, deploy, and scale models.
This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 20% travel.
About the Role
Key Responsibilities
- Design and implement intelligent, self-healing data pipelines that leverage AI/ML for automated data quality monitoring, anomaly detection, and remediation.
- Build and maintain centralized feature stores that enable feature reusability across multiple models and use cases.
- Create curated data repositories optimized for data science/AI workflows, including training datasets, evaluation datasets, and production serving layers.
- Develop automated feature engineering pipelines that transform raw data into analytics-ready features with lineage tracking.
- Partner with Enterprise IT to optimize analytics platform architecture for high-performance data science workloads.
- Build automated pipelines that integrate diverse data sources including sales, CRM, patient claims, real-world evidence, and unstructured data.
- Create self-service data access layers that empower data scientists and analysts to query and extract data independently.
- Establish SLAs for data availability, freshness, and quality; implement monitoring and observability solutions.
Essential Requirements
- Advanced degree in Computer Science, Data Engineering, or related field;
- 10+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure.
- 5+ years leading teams building enterprise-scale data platforms and feature stores.
- Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store).
- Deep expertise in modern data platforms optimized for ML workloads (Databricks, Auto ML, Snowflake, BigQuery).
- Strong proficiency in Python, SQL, Spark/PySpark for large-scale data processing.
- Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines.
- Understanding of data governance, privacy (HIPAA, GDPR), and compliance in life sciences.
Preferred Qualities
- Proven track record of implementing AI/ML-powered automation in data engineering workflows.
- Strategic thinker who can balance innovation (cutting-edge AI tools) with reliability (production stability).
- Builder mindset with ability to create scalable, self-service capabilities that reduce dependency on data engineering.
- Experience in pharmaceutical, healthcare, or life sciences industry.
- Knowledge of streaming technologies, MLOps tools, and data lakehouse architecture.
Novartis Compensation Summary:
The salary for this position is expected to range between $194,600 and $361,400 per year.
The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.
Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves
Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together?
Benefits and Rewards: Learn about all the ways we’ll help you thrive personally and professionally.
Read our handbook (PDF 30 MB)
EEO Statement:
The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.
Accessibility & Reasonable Accommodations
The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [email protected] or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
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Originally posted on Himalayas