Novartis Logo

Novartis

Director, Analytics Engineering (2 Openings)

Posted 23 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

Similar Jobs

13 Minutes Ago
In-Office or Remote
126K-162K Annually
Senior level
126K-162K Annually
Senior level
Cloud • eCommerce • Security • Software • Cybersecurity
Design and operate scalable cloud, Kubernetes, networking, CI/CD, automation, observability, security, and reliability solutions. Lead complex troubleshooting, incident response, root-cause analysis, disaster recovery, data platform integration, and infrastructure improvements. Mentor engineers, establish technical standards, reduce technical debt, and partner cross-functionally to improve developer productivity, platform resilience, and release stability. Participate in rotating on-call coverage for production systems.
Top Skills: Ci/CdCloud InfrastructureContainer SecurityData PipelinesDisaster RecoveryDora MetricsGoldengateIamInfrastructure As CodeJenkinsKubernetesLinuxNetworkingObservabilityOciOkeSoc 2
28 Minutes Ago
In-Office or Remote
Senior level
Senior level
Artificial Intelligence • Fintech • Software • Financial Services
Designs and ships production multi-agent AI systems for KYB, underwriting, case review, and risk monitoring. Owns agent architecture, retrieval, tool integrations, evaluations, observability, MLOps, reliability, and compliance guardrails. Requires strong Python engineering, agent framework expertise, distributed systems experience, Kubernetes operations, and production LLM deployment skills. Mentors engineers and partners with product, security, compliance, and applied science teams. Remote employees travel to Orlando at least twice annually.
Top Skills: Anthropic ClaudeArgocdAWSBraintrustClaude Agent SdkDatadogEksKafkaKubernetesLangchainLangfuseLanggraphLangsmithLlamaMcpMistralNode.jsOpenaiOpenai SdkOpensearchPgvectorPostgresPythonRedisRedshiftTerraformTypescriptVector Databases
40 Minutes Ago
Remote or Hybrid
193K-319K Annually
Expert/Leader
193K-319K Annually
Expert/Leader
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Owns transformational enterprise sales pursuits from strategic discovery through close and early customer value realization. Leads deal strategy, commercial architecture, executive engagement, cross-functional orchestration, negotiations, and handoff to customer success. Develops transformation hypotheses with platform consultants, creates innovative investment structures, aligns partners and internal teams, and codifies pursuit best practices. Requires extensive enterprise software sales, large-deal pursuit, deal structuring, corporate strategy, or complex transaction experience.
Top Skills: Enterprise ArchitectureHyperscalersServicenowServicenow Ai Platform

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account