分析工程总监 (2 个职位)
Director, Analytics Engineering (2 Openings)
Band
Level 6职位描述摘要
诺华有一个令人兴奋的职位机会,是数据分析工程总监。该职位负责构建下一代、基于人工智能的自动化数据管道和可扩展的数据存储库,以实现企业级的数据科学和分析。通过利用先进的AI技术、现代数据工程工具和特征工程平台,这位总监创建自助式、可分析的数据集和企业级特征存储库,使专业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。
该职位可以远程在美国任何地方办公(根据法律实体可能有一些限制)。请注意,此职位不会提供搬迁支持。工作时间安排和出差(国内和/或国际)将由招聘经理确定。该职位需要20%的出差。
有2个职位空缺。职位描述
主要职责:
- 设计和实现智能的、自我修复的数据管道,利用AI/ML进行自动化数据质量监控、异常检测和修复。
- 构建和维护集中式特征存储库,实现多个模型和用例之间的特征重用。
- 创建优化的数据存储库,适用于数据科学/AI工作流程,包括训练数据集、评估数据集和生产服务层。
- 开发自动化的特征工程管道,将原始数据转换为可分析的特征,并具备血缘追踪功能。
- 与企业IT合作,优化分析平台架构,以支持高性能的数据科学工作负载。
- 构建自动化管道,集成多种数据源,包括销售数据、CRM、患者索赔、真实世界证据和非结构化数据。
- 创建自助式数据访问层,使数据科学家和分析师能够独立查询和提取数据。
- 建立数据可用性、新鲜度和质量的服务水平协议(SLA);实施监控和可观测性解决方案。
关键要求
- 计算机科学、数据工程或相关领域的高级学位;
- 7年以上数据工程、机器学习/AI工程或分析基础设施经验。
- 5年以上领导团队构建企业级数据平台和特征存储库的经验。
- 精通特征存储技术(Feast、Tecton、SageMaker Feature Store、Databricks Feature Store)。
- 深厚的实践经验。
查看英文原文
Band
Level 6Job Description Summary
Novartis has an exciting opportunity for a Director, Analytics Engineering. 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.
There are 2 positions available.Job Description
Major accountabilities:
- 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;
- 7+ 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.
To learn more about the culture, rewards and benefits we offer our people click here.
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, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.
Accessibility and 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 in order to perform the essential functions of a position, please send an e-mail to 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.
Salary Range
$194,600.00 - $361,400.00Skills Desired
Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series AnalysisOriginally posted on Himalayas