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Novartis

Associate Director, Data Engineering Lead

Posted 2 Days Ago
Be an Early Applicant
In-Office or Remote
Hiring Remotely in USA
153K-283K Annually
Senior level
In-Office or Remote
Hiring Remotely in USA
153K-283K Annually
Senior level
Lead enterprise data engineering standards, governed pipelines, data contracts, observability, quality controls, lineage, testing, and automation. Partner with governance, privacy, architecture, modeling, and platform teams to deliver reliable, compliant, AI-ready data products. Monitor operational performance and resolve pipeline and data reliability issues across complex enterprise environments.
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Job Description Summary

#LI-Onsite
Location: East Hanover, New Jersey
Novartis is unable to offer relocation support: please only apply if accessible.
Company will not sponsor visas for this position.
The preferred location for this role is East Hanover, New Jersey site but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover, New Jersey site for periodic live meetings will be at the employee’s expense. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager.
Ready to build the foundation that powers trusted, AI-ready data at scale? As Associate Director, Data Engineering, you will play a pivotal role in shaping how enterprise data is engineered, governed, and delivered across Novartis. Working at the intersection of data platforms, governance, and innovation, you will establish the standards, controls, and engineering capabilities that enable reliable, compliant, and high-quality data products. This is an exciting opportunity to influence enterprise-wide data strategy, drive modern DataOps practices, and help accelerate data-driven decision making that ultimately supports better outcomes for patients worldwide.


 

Job Description

Key Responsibilities

  • Define and enforce enterprise standards for data engineering, pipeline reliability, and production controls.

  • Design and oversee scalable, governed data pipelines supporting critical business and data domains.

  • Lead the enterprise data contract lifecycle, including review, approval, governance, and enforcement.

  • Implement data observability capabilities across monitoring, anomaly detection, service levels, and operational alerting.

  • Establish controls that ensure critical data elements remain traceable, validated, and protected.

  • Develop safeguards that prevent incomplete, inaccurate, or non-compliant data from reaching downstream systems.

  • Partner with data modeling teams to align engineering implementation with approved enterprise data models.

  • Collaborate across governance, privacy, architecture, and platform teams to enable compliant data delivery.

  • Drive automation for deployment, validation, metadata capture, lineage generation, testing, and reporting.

  • Monitor operational performance and lead resolution of pipeline, contract, and data reliability issues.

Essential Requirements

  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Management, Engineering, Analytics, or a related field.

  • 5+ years of experience in data engineering, data governance, data architecture, data product management, or enterprise data platform delivery.

  • Experience designing, building, or governing enterprise data pipelines, data products, data platforms, or data integration capabilities.

  • Direct experience with data contracts, schema validation, data pipeline monitoring, data observability, or data product certification.

  • Experience working in complex enterprise environments with multiple data producers, consumers, vendors, platforms, and governance stakeholders.

Desirable Requirements

  • Advanced degree or relevant cloud, data engineering, data management, or architecture certification.

  • Experience supporting regulated, privacy-sensitive, or compliance-driven data environments.

The salary for this position is expected to range between $152,600 - $283,400 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

$152,600.00 - $283,400.00


 

Skills Desired

Cross-Functional Collaboration, Customer Engagement, Customer Insights, Data Analytics, Digital Marketing, Market Research, Media Campaigns, Product Marketing, Stakeholder Engagement, Stakeholder Management, Team Leadership, Waterfall Model

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