Data Operations Manager, Digital Finance

Salary Range:

€40,500.00 - €75,300.00

Job Description Summary

#LI-Hybrid
This role is based in Barcelona, Spain. Novartis is unable to offer relocation support for this role: please only apply if this location is accessible for you.
Step into a pivotal role where data meets strategy. As the Data Operations Manager in Digital Finance, you’ll be at the heart of transforming financial data into actionable insights. You’ll lead the operational lifecycle of finance data products, ensuring accuracy, scalability, and seamless collaboration across technical and business teams. This is your opportunity to impact how Novartis leverages data to drive smarter financial decisions and deliver real impact across the organisation.

Job Description

Responsibilities:                                                                                         

• Serve as the primary liaison across various stakeholders: Finance, Digital teams, and DDIT to align and operate business data product operations.
• Lead and support end-to-end operational activities of enterprise Finance data lake, lakehouse and warehouse products.
• Build knowledge of Finance processes, source systems, data flows and platform capabilities, taking on increasing ownership of defined operational areas.
• Monitor scheduled data loads, pipelines, interfaces, completeness, performance and services across monthly close, planning, forecasting and other critical Finance cycles.
• Execute and progressively automate reconciliations, control checks and data-quality rules covering accuracy, completeness, timeliness, consistency and integrity, with audit-ready evidence.
• Triage incidents and data-quality exceptions; capture business impact, perform first-line diagnosis, coordinate resolution and maintain transparent status communication.
• Maintain SOPs, support models, escalation paths, load calendars, dependency maps, known-error records and recovery procedures.
• Manage and support governed master data access workflows, security groups, data-sharing reviews, retention, archival and deletion in line with privacy, security and records-management requirements.
• Support AI and agent-ready data operations by validating that approved data sources, semantic context and metadata are current, traceable and accessible within defined entitlements.
• Collaborate cross-product operational changes through proactive communication across Digital Finance product teams and engage respective stakeholders.
• Engage Finance users, Product teams through clear communications, knowledge articles and training, and channel recurring feedback into the backlog.

Essential for the role:

• Bachelor’s or master’s degree in computer science, Engineering, Data Science, or a related field.
• Typically 2-3 years of experience in product operations, ideally within data platforms and Agile environments.
• Proven ability to manage timelines, resources, and deliverables across complex data product lifecycles.
• Strong stakeholder engagement skills, translating business needs into actionable operations solution requirements.
• Experience coordinating cross-functional teams and managing scopes with stakeholders and technical partners.
• Familiarity with finance domain processes and systems; understanding of financial data flows is a plus.
• Solid grasp of modern data architectures including Data Lake, Lakehouse, and Data Mesh.
• Experience with T-SQL, data warehouses (e.g., Snowflake, Databricks), and ETL pipelines; understanding of BI tools and data visualization concepts is a plus.
• Foundational GenAI and AI-agent fluency, including safe use of approved tools, instruction quality, human review, data privacy and escalation of unexpected outputs.

 

Desirable for the role:

• Experience working in multi-functional teams across various organizational levels and business domains.
• Familiarity with data management capabilities such as data catalogues, semantic layers, master or reference data and data contracts.

Benefits & Rewards

At Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen.

Expected Annual Base Salary Range for role:  40,500 – 75,300 EUR gross.

The base salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically.

In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters.

The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and minimum 14 weeks paid parental leave.

Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics.

Read our brochure to learn more about our global total rewards offering:

https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf

Note: Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process.

Commitment to Diversity and Inclusion / EEO paragraph

Novartis is committed to building an outstanding, inclusive work environment and diverse teams’ representative of the patients and communities we serve.

 

Skills Desired

Critical Thinking, Data Visualization, Employee Engagement, Insight Generation, Managing Ambiguity, Market Understanding, Process Optimization