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 of Data Analyst involves developing and implementing a data governance framework to ensure data accuracy, completeness, and integrity.
Key responsibilities include establishing data quality monitoring processes, identifying root causes of inconsistencies, and collaborating with cross-functional teams to resolve data gaps.
The ideal candidate should have expertise in SQL and Python for data manipulation and automation, be comfortable working with large datasets, and have experience in designing dashboards with actionable recommendations.
Responsibilities also include creating documentation, customized reports, and dashboards, as well as extracting data from databases like Redshift and MongoDB.

Requirements:

Candidates must have 3+ years of work experience in a data analysis or data quality role.
Strong technical skills in data analysis are required, with proficiency in SQL and Python.
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.
Candidates should have experience writing process documentation and data collection guidelines.
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) and workflow automation tools such as Apache Airflow is beneficial.
Experience working in an Agile or product-driven environment and familiarity with data privacy and compliance regulations (e.g., GDPR, HIPAA) are also nice to have.