Clinical Data Engineer RDX (DQ)

The Clinical Data Engineer (Data Quality) role is responsible for ensuring the accuracy, completeness, consistency, and reliability of data within key systems. This role is critical for maintaining the integrity of clinical, portfolio management, and product submission data, enforcing data quality principles, and bolstering regulatory compliance efforts. The ideal candidate should possess strong knowledge of the role data quality plays in the data lifecycle and ensures that data inputs and outputs meet all specified Data Quality (DQ) criteria.

Through close collaboration with study leads, regulatory experts, and DigitalX professionals, this role establishes and upholds robust Data Quality standards that align with business objectives, regulatory mandates, and industry standards. Expertise in Data Quality, Data Governance, and adeptly managing governance processes is essential for maintaining the integrity of data assets. This role holds a pivotal position in advancing the life sciences company's mission by using data to drive the facilitation of data-driven decision-making processes, expediting drug discovery initiatives, and bolstering regulatory compliance efforts.

Responsibilities And Accountabilities

• Responsible for Data Quality business rules implementation, DQ Analysis, and DQ Remediation activities.
• DQ Checks Implementation :
• Participate as needed in the creation of data quality checks and standards for multiple source systems.
• Implement business data quality checks on the SaaS platform (E.g. Databricks), working in conjunction with business teams, and data lake teams.
• Team-up with Data Lake teams in orchestration of DQ checks code across the various environments, leading to a successful Production deployment.
• Experience with unit testing and test-driven development (TDD), Test Scripts Execution and Approval in Lifecycle Management.
• Perform required validation and testing, to ensure DQ output matches the rules' criteria, ensuring data accuracy, integrity and consistency across systems and applications.
• Collaborate with external vendors and partners to optimize data quality services.
• DQ Support and Remediation :
• Identify, document and track DQ violations and defects, work with development, data lake teams to resolve issues.
• Define, monitor, and report on Data Quality metrics.
• Collaborate internally in the creation of repeatable processes and continuous improvements.
• Lead DQ investigations to analyse issues and determine business impact.
• Establish ongoing data quality monitoring to ensure DQ issues are quickly identified and resolved.
• Provide post-release support related to Data Quality problems, workflows, and DQ batch job runs.

Responsibilities

 Other Responsibilities :

Required Qualifications

Preferred Qualifications

Category

Astellas is committed to equality of opportunity in all aspects of employment.

EOE including Disability / Protected Veterans

Skills Required

Google Cloud Platform, Tableau, Sql, ELT, Data Quality, Informatica Data Quality, Qlik, Data Analysis, Databricks, Data Governance, Azure, Talend, Aws, Etl