Staff Data Modeler

ANSR is hiring for one of its clients.

About ANSR MedTech:

Who We Are:

ANSR MedTech Capability Center is a new global innovation hub being established in India for a Fortune 100 Fastest-Growing Company in the MedTech sector. Built in partnership with ANSR, the center draws on ANSR's proven experience in establishing and scaling high-performance Global Capability Centers (GCCs) for leading global enterprises.

ANSR MedTech center brings together world-class engineering, product, and technology talent to build next-generation healthcare platforms and solutions that power global operations.

Our Vision:

To build a next-generation MedTech capability center that powers global healthcare innovation. We envision:

• High-impact innovation hubs shaping global product and technology roadmaps
• Centers that go beyond support functions to drive core engineering and platform development
• Sustainable, scalable ecosystems that nurture world-class MedTech talent
• Capability centers that directly influence patient outcomes worldwide

At its core, the ANSR MedTech Capability Center is about enabling innovation that touches lives at scale.

Job Title: StaffData Modeler

Location: Bengaluru, India

About the Role:

The StaffData Modeler is responsible for designing, documenting, and maintaining enterprise data models that support analytics, reporting, AI, and operational data products. This role safeguards data integrity, lineage, consistency, and reproducibility across the data ecosystem.

The Data Modeler works closely with Data Engineering, Data Governance, Analytics Engineering, Power BI, and business stakeholders to translate business processes and information needs into scalable conceptual, logical, and physical data models.

Responsibilities:

Enterprise Data Modeling:

• Design and maintain conceptual, logical, and physical data models for enterprise data domains.
• Develop dimensional, normalized, and analytical data structures that support reporting, dashboards, data science, and AI use cases.
• Define business entities, relationships, hierarchies, keys, grain, master data structures, and reusable data domains.
• Create and maintain source-to-target mappings, transformation rules, metric definitions, and data model documentation.
• Standardize modeling approaches across domains, platforms, and consumption layers.

Data Integrity, Lineage & Reproducibility:

• Safeguard data consistency, lineage, traceability, and reproducibility across analytical data products.
• Partner with Data Engineering to ensure pipeline implementations accurately reflect approved data models and business rules.
• Support reconciliation and validation across source systems, curated layers, semantic models, and reporting outputs.
• Assess downstream impacts of schema changes, model changes, and business rule updates.
• Document assumptions, constraints, quality issues, and data dependencies.

Governance, Metadata & Standards:

• Partner with Data Governance teams to establish data definitions, metadata standards, naming conventions, and modeling guidelines.
• Support cataloging, lineage capture, and metadata management in enterprise governance tools.
• Create reusable modeling patterns and reference designs for common data domains.
• Ensure data models align with privacy, security, and regulatory expectations in a governed environment.

Cross-Functional Collaboration:

• Work with business stakeholders to understand business processes, reporting needs, and analytical consumption patterns.
• Partner with Data Engineers, Data Scientists, Analytics Engineers, and Power BI Engineers to ensure models are fit for purpose.
• Collaborate with Enterprise Architecture and platform teams to align data models with enterprise architecture standards.
• Participate in design reviews, sprint ceremonies, peer reviews, and delivery forums.

Required Qualifications:

• Bachelor's or Master's degree in computer science, information systems, engineering, data management, or a related field, or equivalent practical experience.
• 8+ years of experience in data modeling, data architecture, enterprise data management, or analytics engineering.
• Strong experience with conceptual, logical, and physical data modeling.
• Strong knowledge of dimensional modeling, Kimball methods, star schemas, snowflake schemas, normalized models, and analytical data structures.
• Strong SQL skills and deep understanding of relational and cloud data platforms.
• Experience designing models for enterprise-scale analytics, reporting, and data product consumption.
• Knowledge of metadata management, master data management, data governance, and lineage practices.
• Ability to translate business processes and requirements into scalable data structures.

Preferred Qualifications:

• Experience with Databricks Lakehouse architecture, lakehouse modeling patterns, or medallion architecture.
• Experience working with SAP data models, SAP BI, ERP, Commercial, Finance, Order-to-Cash, or Supply Chain domains.
• Experience using data modeling tools, metadata tools, or governance platforms such as Atlan, Alation, Collibra, Erwin, or equivalent.
• Experience in healthcare, life sciences, medical devices, or other regulated industries.
• Exposure to semantic modeling for Power BI, Microsoft Fabric, or enterprise BI platforms.
• Understanding of data quality frameworks and reference data management.

Skills/Competencies:

• Strong systems thinking and ability to connect source systems, business processes, curated data layers, and consumption needs.
• High attention to detail with a strong focus on consistency, definitions, lineage, and documentation.
• Ability to influence engineering and business stakeholders through clear data design rationale.
• Strong collaboration skills across global data, analytics, governance, and business teams.
• Ability to balance enterprise standards with pragmatic delivery needs.