Data Steward
4 weeks ago
We are seeking a highly motivated Data Steward to join our team to support our
pharmaceutical customer. The ideal candidate will play a crucial role in ensuring the integrity,
quality, and usability of client organization's data assets, specifically within the life sciences
domain. This is a business-facing role requires a deep understanding of technical aspects
related to data management and the Data Steward will work independently with minimal
supervision and must possess excellent communication skills to effectively collaborate with
various stakeholders.
Responsibilities:
Independently manage and oversee the organization's data assets to ensure accuracy,
completeness, and consistency.
Collaborate with business stakeholders to understand their data requirements,
challenges, and objectives.
Develop and implement data quality standards, policies, and procedures to improve
data governance and compliance within the company.
Conduct data profiling and analysis specific to pharmaceutical data to identify data
quality issues and recommend corrective actions.
Act as a liaison between business users and technical teams to translate business
requirements into technical specifications.
Monitor data flows and processes to identify areas for improvement and
optimization.
Provide training and support to business users on data management best practices
and tools.
Stay informed about industry trends and best practices in data management and
governance within the life sciences domain.
Participate in cross-functional teams and projects to drive data-related initiatives
forward within the pharmaceutical context.
Maintain documentation related to data policies, procedures, and standards within
the pharmaceutical industry.
Requirements:
Proven experience (5-10 years) as a Data Steward or similar role in a business-
facing capacity.
Strong understanding of business processes and workflows, with the ability to align
data management initiatives with industry-specific objectives
Familiarity with data governance frameworks, data quality concepts, and data
management tools within the pharmaceutical context.
Excellent communication skills, with the ability to effectively communicate
technical concepts to non-technical stakeholders.
Ability to work independently with minimal supervision, prioritize tasks, and
manage time effectively.
Proficiency in data analysis techniques and tools for data profiling and quality
assessment.
Strong problem-solving skills and attention to detail within the pharmaceutical or
life sciences domain.
Exposure to data management tools like Reltio and Collibra is considered an
advantage.
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