• Solid expertise in data modeling, with considerable experience in database technologies, particularly Azure Databricks, Azure Synapse, and Azure Data Factory, to support business intelligence, analytics, and reporting initiatives.
• Strong understanding of best practices in data modeling to ensure that models are scalable, efficient, and maintainable.
Qualifications:
• 10+ years of overall experience, with strong domain knowledge in Clinical Research Organizations and Biopharmaceutical services preferred.
• Proven track record of designing, developing, and maintaining complex logical data models in multiple subject areas.
• Proficiency in data modeling tools such as ER/Studio, ERwin or PowerDesigner.
• Strong proficiency in SQL for querying and manipulating data and experience with relational database management systems (RDBMS).
• Proven ability to work effectively with Data Governance Analysts, Business Analysts, Data Analysts, Database Developers, and Report Developers to ensure alignment and successful project delivery.
• Familiarity with data governance frameworks and regulatory requirements, ensuring data models adhere to organizational policies and standards.
• Understanding of clinical research processes, clinical trial data and regulatory requirements is not a must to have but it is a plus.
• Self-starter with an ability to work collaboratively in a fast-paced and team-oriented environment.
• Working knowledge of any agile tools like Jira/Confluence/Asana is preferred.
Key Responsibilities:
• Responsible for data transformation, create data models and data marts, and coordinate scheduling to meet project deadlines.
• Collaborate closely with the Enterprise Information Management (EIM) Team on data loading, validation strategies, data quality analysis, issue resolution, unit testing, and release management.
• Conduct data profiling and analysis to assess data quality, consistency, and integrity, leveraging dimensional modeling techniques where appropriate.
• Create and maintain data mapping documents to support ETL processes and data integration efforts to ensure clarity and consistency.
• Responsible for data migration and data modernization efforts within Enterprise Data Lake.
• Focus on development of data pipelines, focusing on source-to-target mappings, ETL process implementation, and the management of sessions and workflows.
• Implement and enforce data modeling standards, best practices, and guidelines across the organization, promoting consistency and reusability.
• Collaborate with cross-functional teams to integrate data from multiple sources and systems, ensuring data consistency and accuracy.
• Conduct impact analysis of proposed changes to data models and databases, evaluating potential risks and implications.
• As part of sanity check, validate the tables and views after development to ensure the developers effectively applied the logic we provided in the logical model.
• Perform performance tuning and optimization of data models and database queries, ensuring efficient data retrieval and processing.
• Analyze and resolve data modeling-related issues, addressing data quality concerns and discrepancies as they arise.
• Present ideas and findings to all stakeholders to ensure solutions meet business needs and requirements.
• Proactively communicate changes that may affect integration interfaces well in advance.