Data Modeler (Remote)

Job Description: Data Modeler (Offshore)

About Client

A leading multinational IT services and consulting company specializing in digital transformation, cloud solutions, and AI-driven innovation. With a strong global presence, the company partners with enterprises across various industries to deliver cutting-edge technology solutions.

Must Have Skills:

1. 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.
2. Strong understanding of best practices in data modeling to ensure that models are scalable, efficient, and maintainable.
3. 10+ years of overall experience, with strong domain knowledge in Clinical Research Organizations and Biopharmaceutical services preferred.
4. Proven track record of designing, developing, and maintaining complex logical data models in multiple subject areas.
5. Proficiency in data modeling tools such as ER/Studio, ERwin, or PowerDesigner.
6. Strong proficiency in SQL for querying and manipulating data and experience with relational database management systems (RDBMS).
7. 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.
8. Familiarity with data governance frameworks and regulatory requirements, ensuring data models adhere to organizational policies and standards.
9. Understanding of clinical research processes, clinical trial data, and regulatory requirements is not a must to have but it is a plus.
10. Self-starter with an ability to work collaboratively in a fast-paced and team-oriented environment.
11. Working knowledge of any agile tools like Jira/Confluence/Asana is preferred.

Key Responsibilities:

1. Responsible for data transformation, create data models and data marts, and coordinate scheduling to meet project deadlines.
2. Collaborate closely with the Enterprise Information Management (EIM) Team on data loading, validation strategies, data quality analysis, issue resolution, unit testing, and release management.
3. Conduct data profiling and analysis to assess data quality, consistency, and integrity, leveraging dimensional modeling techniques where appropriate.
4. Create and maintain data mapping documents to support ETL processes and data integration efforts to ensure clarity and consistency.
5. Responsible for data migration and data modernization efforts within Enterprise Data Lake.
6. Focus on development of data pipelines, focusing on source-to-target mappings, ETL process implementation, and the management of sessions and workflows.
7. Implement and enforce data modeling standards, best practices, and guidelines across the organization, promoting consistency and reusability.
8. Collaborate with cross-functional teams to integrate data from multiple sources and systems, ensuring data consistency and accuracy.
9. Conduct impact analysis of proposed changes to data models and databases, evaluating potential risks and implications.
10. 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.
11. Perform performance tuning and optimization of data models and database queries, ensuring efficient data retrieval and processing.
12. Analyze and resolve data modeling-related issues, addressing data quality concerns and discrepancies as they arise.
13. Present ideas and findings to all stakeholders to ensure solutions meet business needs and requirements.
14. Proactively communicate changes that may affect integration interfaces well in advance.