Senior Analyst, Brand Data Enablement, Data Integrations

Job Description Summary

We are seeking a Senior Analyst, Brand Data Enablement to support the migration, integration, and continuity of brand-level data enablement deliverables as part of a large-scale acquisition and platform change programs. This role ensures that the brand data products, operational datasets, and performance reporting pipelines are assessed, translated, and re-established within the target organization's / target platform’s data and infrastructure ecosystem — without disruption to brand teams' decision-making capabilities.
The individual will work across brand operations, data engineering, and analytics functions from both entities, ensuring that commercial datasets, brand KPI frameworks, and enablement workflows are mapped, migrated, and validated through evolving infrastructure landscapes. This role requires a blend of data enablement expertise, pharma commercial domain knowledge, and the structured execution discipline essential to data & platform integration programs.

Job Description

Location: Hyderabad #Hybrid

Key Responsibilities

• Brand Data Discovery & Inventory: Catalog all brand-level data enablement deliverables — including datasets, KPI outputs, recurring reports, SOPs, and operational workflows. Document data sources, refresh cadence, business owners, downstream consumers, and quality standards for each deliverable.

  
  
  

• Data Enablement Migration: Design, develop, and maintain data enablement solutions that translate brand performance datasets into the target organization's infrastructure. Ensure that commercial data feeds (e.g., prescription data, promotional activity, patient-level data, specialty pharmacy, affiliations) are re-mapped and re-connected on the target platform with full fidelity.

  
  
  

• Cross-Entity Dataset Reconciliation: Map commercial data sources to the target organization's equivalent datasets (e.g., patient-level data, prescription audits, promotional feeds, third-party syndicated data). Identify gaps, overlaps, and definition conflicts. Produce field-level crosswalk documents and drive alignment with relevant stakeholders.

  
  
  

• Quality & SOP Management: Maintain and adapt standard operating procedures (SOPs) and quality checklists for all brand enablement outputs during migration. Ensure that data quality checkpoints are preserved or enhanced as deliverables move from legacy to target infrastructure. Define acceptance criteria for each migrated deliverable.

  
  
  

• Validation & Delivery: Deliver migrated brand enablement outputs as per agreed timelines, accuracy, and quality standards. Execute side-by-side validation of legacy vs. migrated outputs — including metric reconciliation, trend continuity, and edge case testing. Coordinate with brand stakeholders for UAT and sign-off.

  
  
  

• Stakeholder Communication & Coordination: Maintain exemplary communication with all partners — brand teams, data engineering, analytics, and leadership — through regular updates focused on migration progress, quality metrics, risks, and key milestones. Support leads with appropriate documentation throughout the delivery lifecycle.

  
  
  

• Knowledge Sharing & Continuous Improvement: Participate in and contribute to cross-team knowledge sharing sessions to propagate migration learnings, improve quality deliverables, and accelerate enablement for all brands/teams transitioning to the new platform. Identify opportunities to standardize and improve brand data products enabled by platform consolidation.

  
  
  

Essential Requirements:

• 3–5 years of experience in a data enablement role, preferably in US pharma commercial operations.

  
  
  

• Familiarity with data tools such as SQL, Dataiku, Power BI, Python, and project management tools (e.g., Jira).

  
  
  

• Exposure to US pharma commercial datasets such as patient-level data (APLD), specialty pharmacy (SP), prescription audits (e.g., IQVIA Xponent), claims/diagnosis data, promotional activity, HCP affiliations, and CRM data.

  
  
  

• Experience developing and coordinating project plans across design, development, and production stages with delivery against defined KPIs.

  
  
  

• Strong collaboration skills with cross-functional teams including brand, technical, analytics, and data engineering functions.

  
  
  

• Strong communication and presentation skills with good learning agility and an analytical mindset.

  
  
  

Desirable Requirement:

• Demonstrated experience in migrating or re-building brand data enablement deliverables during a platform transition, data and platform integration, or large-scale infrastructure change — not just steady-state delivery.

  
  
  

• Proven ability to map and reconcile commercial pharma datasets across two entities or platforms — including field-level crosswalks for prescription data, patient-level data, promotional feeds, and third-party syndicated sources.

  
  
  

• Hands-on experience with data quality management during transitions — maintaining SOPs, quality checklists, and validation protocols while underlying infrastructure is changing.

  
  
  

Commitment to Diversity & Inclusion

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

Accessibility and accommodation

Novartis is 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 recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Skills Desired

Advertising Campaigns, Alteryx, Analytical Thinking, Brand Awareness, Business Networking, Curiosity, Digital Marketing, Marketing Communications, Marketing Plans, Marketing Strategy, Media Campaigns, Process Documentation, Statistical Analysis, Strategic Marketing