Role Description
The Data Management team is responsible for developing, governing, and operationalizing IQVIA Digital's industry-leading healthcare and consumer data assets, which serve as the foundation for our products, analytics, business intelligence, and AI-enabled solutions. Working closely with Product and Technology teams, the organization ensures the quality, integrity, security, and scalability of data across the ecosystem.
Job Overview: Designs and manages the foundational analytical data structures that enable scalable business intelligence, self-service analytics, and consistent reporting across the organization. Serves as a key partner between business and technical teams, ensuring data is modeled and governed in a way that is intuitive for consumers, aligned with business needs, and sustainable as analytical capabilities mature.
Essential Functions
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Designs, develops, and maintains semantic data models, including facts, dimensions, hierarchies, relationships, and business metrics that support enterprise reporting and analytics.
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Partners with business intelligence developers, analysts, and stakeholders to understand analytical requirements and translate them into scalable, reusable data structures.
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Defines and implements data modeling standards and best practices, including dimensional modeling, slowly changing dimensions, historical data management, and conformed dimensions.
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Establishes and maintains business-friendly semantic layers that simplify access to complex healthcare and product datasets while preserving data accuracy and consistency.
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Collaborates with software engineering, data platform, and business teams to ensure semantic models align with source system design, enterprise data architecture, and organizational reporting needs.
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Partners with analysts and business stakeholders to operationalize approved metric definitions and business rules within scalable, reusable semantic models.
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Evaluates and optimizes model performance, scalability, and usability to support both dashboard-based reporting and ad hoc self-service analysis.
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Participates in data architecture discussions and provides guidance on data design decisions that impact reporting, analytics, and data consumption.
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Identifies opportunities to improve data accessibility, model reusability, and overall analytical maturity across the organization.
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Validates data quality and model integrity through testing, monitoring, and collaboration with engineering and analytics teams.
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Supports governance efforts by establishing standards for data definitions, metric calculation, documentation, and semantic layer usage.
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Serves as a technical advisor on analytics initiatives, helping teams understand the implications of data design decisions on long-term scalability and maintainability.
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Identifies opportunities to extend analytical data models and curated datasets to support self-service analytics, AI-assisted data exploration, and other emerging data consumption patterns.
Qualifications
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Bachelor's Degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent experience.
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5+ years of experience in analytics engineering, business intelligence engineering, data modeling, data architecture, or a related field.
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Strong experience designing and implementing dimensional data models, including fact and dimension tables, star schemas, and semantic layers.
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Demonstrated understanding of data warehouse concepts and best practices, including slowly changing dimensions, historical tracking, surrogate keys, and data lineage.
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Experience developing and optimizing data models that support business intelligence and self-service analytics solutions.
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Proficiency in SQL and experience working with large, complex datasets.
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Experience developing analytical data models within modern cloud data platforms such as Snowflake, BigQuery, Redshift, Synapse, or Databricks.
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Experience optimizing analytical data structures for performance, scalability, and self-service consumption.
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Experience partnering with business stakeholders to translate analytical requirements into scalable technical solutions.
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Strong understanding of data governance, metric standardization, and analytical best practices.
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Experience collaborating with software engineering, data engineering, and analytics teams in a cross-functional environment.
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Ability to balance technical design considerations with business usability and accessibility requirements.
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Strong written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
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Experience with healthcare data, product data, or other complex domain-specific datasets preferred.
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Experience supporting Power BI or Tableau semantic models, tabular models, or equivalent business intelligence technologies preferred.
Benefits
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The potential base pay range for this role, when annualized, is $77,800.00 - $194,400.00.
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The actual base pay offered may vary based on a number of factors including job-related qualifications such as knowledge, skills, education, and experience; location; and/or schedule (full or part-time).
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Dependent on the position offered, incentive plans, bonuses, and/or other forms of compensation may be offered, in addition to a range of health and welfare and/or other benefits.
