Description:

Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster.
The company is one of the fastest-growing SaaS companies in history, surpassing $2B in revenue in the last fiscal year with extensive growth potential ahead.
Veeva is a public benefit corporation (PBC), legally bound to balance the interests of customers, employees, society, and investors.
The company supports flexible work arrangements, allowing employees to work from home or in the office.
The role is for a detail-oriented and experienced Data Analyst to join the Veeva Link product team.
Responsibilities include developing and implementing a data governance framework, ensuring data accuracy, completeness, and integrity.
Key tasks involve establishing data quality monitoring processes, identifying root causes of inconsistencies, and collaborating with cross-functional teams to resolve data gaps.
Expertise in SQL and Python for data manipulation and automation is required.
The candidate should be comfortable working with large datasets, designing dashboards with actionable recommendations, and applying statistical techniques to assess and enhance data quality.
Experience in creating documentation and contributing to data governance policies and best practices is essential.

Requirements:

Candidates must have 5+ years of work experience in a data analysis or data quality role.
Strong technical skills in data analysis, with proficiency in SQL and Python are required.
Experience in data storage and processing on cloud platforms such as AWS, GCP, or Azure is necessary.
Strong problem-solving skills and experience working with cross-functional teams are essential.
Experience writing process documentation and data collection guidelines is required.
A university degree in medicine or life sciences is a nice to have.
Understanding of healthcare, life sciences, or pharmaceutical industry data is preferred.
Experience with data visualization tools to create dashboards and reports is a plus.
Familiarity with data engineering concepts (ETL, data pipelines) is beneficial.
Experience with workflow automation tools such as Apache Airflow is a nice to have.
Experience working in an Agile or product-driven environment is preferred.
Familiarity with data privacy and compliance regulations (e.g., GDPR, HIPAA) is advantageous.