- The Business Data Analyst contributes significantly to the mission to supercharge our data, and is responsible for ensuring data domains and products are defined and delivered with findability, accessibility, interoperability supportability, usability and quality in mind
- As a Business Data Analyst you will guide the information architecture, data standards, and quality of the data products on the Development Data Fabric in alignment with the data mesh architectural plan
Key responsibilities:
Strategy - Work with peers and colleagues in Development Digital and Tech to define a framework for consistently and efficiently capturing data models , data dictionaries, business and technical metadata and requirements for moving processing protecting and using data within the Development Data Fabric. Actively seek out opportunities to refine this framework and automate the creation/maintenance of information and artefacts. Keep abreast of emerging trends in data management technologies and integrated them into the target designs where appropriate
Analysis - Understand the systems and processes in Pharma R&D where data is generated, used and reused to enable operations, inform decisions and drive scientific innovations. Reverse engineer analytical use cases into data flows, target data models and data processing requirements. Partner with data product owners in the business and tech teams to document data quality checks and access management requirements. Partner with data quality and governance product owners to surface opportunities to leverage reference data, master data and/or ontology management platforms to drive standardization and interoperability.
Modeling - generate models and associated artefacts to inform requirement and build activities. Work with data product owners and subject matter experts to capture and maintain the metadata required to ensure data released to the Development Data Fabric is Findable, Accessible Interoperable and Reusable (FAIR). Support Data Fabric data processes and produce associated documents.
Lifecycle Management - Support the product and engineering teams during design and build by liaising with the business and technical team to answer key questions and deliver pertinent information. Partner with data stewards and technical support teams during use to investigate data quality and lineage issues. Enable the drive towards and adaptive and automated approaches to data governance and data management.
Basic Qualifications:
Bachelor s Degree in computer science, engineering, or similar discipline
5+ years relevant clinical experience and / or exposure to enterprise architecture in an IT organization
Experience eliciting and documenting user requirements for data and analytics products
Proficient with data modelling and data quality/profiling tools
Experience modelling databases e.g. Snowflake and Synapse
Experience generating modelling artefacts
Understanding of the data mesh framework and its application in Pharma R&D analytics including but not limited to data integration, data governance, data quality, data security, data lineage, data cataloging, data discovery, data access, data sharing, data collaboration, etc.
Experience with Pharma R&D information standards (CDISC, BRIDG, SHARE, ODM, OMAP, FHYR) and data protection obligations.
Track record in delivering business impact through data and analytics enabled solutions.
Excellent relationship management, strong influencing and communication skills at senior level.
Experience with Agile and DevOps
Preferred Qualifications:
Masters or PhD in computer science, engineering or similar discipline
Experience constructing a data fabric or similar architecture
Understanding of where emerging technologies can drive automation in the creation and management of data products
Design and architecture of BI and analytic environments
Enablement of AI/ML users and applications