AD, Tech/Ops Data Partnerships

Novartis

2d•$145,600 - $270,400•Remote

About The Position

This Associate Director role sits within Data Partnerships Operations and reports to the Data Partnerships Leads. The role supports smooth onboarding and ongoing management with data partners/vendors, serving as a day-to-day coordination point across business stakeholders, brands, functions, Data Partnerships, data partner/vendor technical teams, DEO, IM DnA, and cross-functional technical teams. The role requires close alignment with business priorities and operating rhythms to help ensure data is flowing correctly, metadata is captured on data assets, catalogs and inventories remain current, and issues are triaged, escalated, and resolved in a timely manner. The Associate Director will orchestrate technical onboarding in collaboration with DEO, support day-to-day data operations post-go-live, coordinate real-time issue resolution across data partners/vendors and internal teams, track SLA adherence and delivery performance, and maintain the documentation, metadata, catalog inputs, and operational insights needed to strengthen data partner/vendor execution and trusted data asset management.

Requirements

Bachelor's degree in related field is required; Master of Science and/or MBA strongly preferred
Minimum 7+ years of experience in pharmaceutical, healthcare, technology, data, analytics, data partner/vendor operations, data engineering coordination, or consulting.
Experience coordinating smooth technical onboarding, ongoing data partner/vendor management, data delivery, ingestion readiness, metadata alignment, catalog inputs, file formats, delivery requirements, and operational handoffs.
Strong understanding of data quality, data pipelines, issue tracking, SLA management, data partner/vendor documentation, metadata, and data asset inventory processes.
Proven ability to coordinate across business stakeholders, brands, functions, data partners/vendors, Data Partnerships, data engineering, and analytics stakeholders in a fast-paced, matrixed environment requiring timely alignment, escalation, and follow-through.
Ability to manage centralized trackers, operational dashboards, delivery health metrics, recurring issue themes, and performance insights with strong attention to detail.
Excellent communication skills, with the ability to translate technical issues into clear operational implications, risks, decisions, and next steps for business stakeholders, brands, functions, and leadership audiences.
Ability to thrive in a fast-paced environment, manage ambiguity, proactively escalate risks, and drive follow-through to closure.

Nice To Haves

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

Responsibilities

Serve as the day-to-day coordination point across business stakeholders, brands, functions, Data Partnerships, data partner/vendor technical teams, and Novartis data engineering teams, including DEO / IM DnA.
Support smooth technical onboarding in collaboration with DEO, ensuring alignment on data formats, metadata, delivery requirements, catalog inputs, and readiness milestones.
Provide ongoing technical operations support post-go-live, working cross-functionally in the cadence of business stakeholders, brands, and functions to monitor ingestion, confirm data is flowing correctly, track pipeline performance, and coordinate issue resolution.
Maintain and manage a centralized data issue tracker covering both technical and business-related issues, ensuring visibility, ownership, validation, and closure.
Coordinate timely data quality issue resolution across data partners/vendors and internal teams, using business context to prioritize risks, escalate recurring issues, and provide actionable insights to Data Partnerships leadership.
Support working-level data partner/vendor technical relationship management, including frequent operational touchpoints, delivery follow-up, real-time issue triage, escalation, and performance discussions.
Track SLA adherence and delivery performance, proactively flagging risks, recurring gaps, and opportunities to improve reliability.
Maintain data documentation, metadata, data partner/vendor documentation, data asset inventory inputs, catalog updates, onboarding progress, delivery health metrics, and back-end process tracking.