Novartis Logo

Novartis

Director, Analytics Engineering (2 Openings)

Posted 8 Days Ago
Remote
Hiring Remotely in USA
195K-361K Annually
Senior level
Remote
Hiring Remotely in USA
195K-361K Annually
Senior level
Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.
The summary above was generated by AI

Job Description Summary

#LI-Remote
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, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. 


 

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 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.


 

Salary Range

$194,600.00 - $361,400.00


 

Skills 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 Analysis

Novartis San Carlos, California, USA Office

San Carlos, United States, 0

Similar Jobs

55 Minutes Ago
Easy Apply
Remote or Hybrid
Arizona, USA
Easy Apply
16-16 Hourly
Junior
16-16 Hourly
Junior
Automotive • Big Data • Insurance • Software • Transportation
Handle high-volume inbound roadside assistance calls, gather location and vehicle details, dispatch tow and service providers, and support distressed motorists. The role requires empathetic de-escalation, accurate multitasking across digital systems, sound judgment under pressure, reliable schedule adherence, and effective collaboration in a remote contact-center environment.
Top Skills: Crm SoftwareDispatch SoftwareEthernetGmailGoogle ChatGoogle ChromeGoogle DocsGoogle MapsGoogle SheetsGoogle WorkspaceHarverMozilla FirefoxSwoopWindows 11Zoom
55 Minutes Ago
Easy Apply
Remote or Hybrid
Alabama, USA
Easy Apply
16-16 Hourly
Junior
16-16 Hourly
Junior
Automotive • Big Data • Insurance • Software • Transportation
Provides real-time roadside assistance to stranded motorists by gathering location and vehicle details, dispatching tow and service providers, de-escalating stressful calls, documenting interactions, and tracking service progress across digital systems. The role requires empathy, sound judgment, multitasking, reliable schedule adherence, and strong technology skills in a remote contact-center environment. Associates must work full time, support weekend and holiday coverage, complete mandatory training, and provide an approved home-office setup and equipment.
Top Skills: Ai ToolsCrm SoftwareDispatch SoftwareEthernetGoogle ChatGoogle ChromeGoogle MapsGoogle WorkspaceHarverMozilla FirefoxWindows 11Zoom
56 Minutes Ago
Easy Apply
Remote or Hybrid
Florida, USA
Easy Apply
16-16 Hourly
Junior
16-16 Hourly
Junior
Automotive • Big Data • Insurance • Software • Transportation
Provides real-time inbound roadside assistance to stranded motorists by gathering incident details, dispatching service providers, tracking service progress, and de-escalating stressful customer interactions. The role requires multitasking across digital tools, accurate documentation, empathy, sound judgment, and reliable performance in a remote contact-center environment. Associates must maintain a dedicated home workspace, meet strict BYOD and internet requirements, work full time with weekend or holiday availability, and complete mandatory training with full attendance.
Top Skills: Ai ToolsCrm SystemsDispatch SoftwareGmailGoogle ChatGoogle ChromeGoogle DocsGoogle MapsGoogle SheetsGoogle WorkspaceHarver System CheckerMozilla FirefoxSwoopWindows 11Zoom

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account