Data/Business Analyst

About the role

This role focuses on bridging the gap between business needs and technical implementation for data pipelines within the life sciences, agrochemical, and pharma sectors. The analyst will gather requirements from various stakeholders, including source system owners and regulatory bodies, and translate these into detailed epics and stories for development. A key responsibility involves leading backlog refinement sessions to prioritize data ingestion and transformation activities, ensuring clear definitions of work and completion criteria.

A significant part of this position involves ensuring data integrity and regulatory adherence. The analyst will identify and document potential data quality issues, such as normalization problems or governance gaps, and work with data architects to define the transformation pipeline architecture. They will also support the review of data models and validate that all mappings and transformations meet compliance standards, data quality metrics, and analytical readiness.

Success in this role means effectively coaching team members in self-management and organizing high-value increments within sprints, acting as an agile scrum master. It also involves close collaboration with data scientists to define mapping logic for regulatory entities and reviewing quality control pipelines for accuracy. The ideal candidate will ensure that the regulatory and business context is preserved across all transformed datasets, contributing to robust and compliant data solutions.

The compensation for this role is competitive, with a salary range between $92,000 and $149,500 USD.

Skills that matter here

• data analytics: This role requires using data analytics principles to define requirements and validate transformations for regulatory and business contexts.
• data transformation: The analyst will define and document data transformation pipeline architecture and ensure transformations meet compliance and quality standards.
• data quality frameworks: Expertise in data quality frameworks is essential for identifying issues and ensuring data integrity across datasets.
• Databricks: Hands-on experience with Databricks is a requirement for this position, indicating its use in the data environment.
• metadata management: Familiarity with metadata management principles is needed to support data governance and architectural definitions.
• data governance: The role involves identifying data governance gaps and ensuring compliance with established principles.

Who this role suits

• A person who thrives on translating complex business and regulatory needs into clear, actionable technical requirements.
• Someone with a meticulous eye for detail, capable of identifying and documenting data quality issues and governance gaps.
• An individual who enjoys leading agile processes, coaching teams, and facilitating collaboration across diverse technical and domain experts.
• A proactive and adaptable professional comfortable navigating ambiguity and evolving project priorities in a data-intensive environment.

From the employer

• Collaborate with source system owners and regulatory stakeholders to gather and refine data pipeline requirements
• Translate data pipeline requirements into epics and stories ready for refinement in Jira
• Lead backlog refinement sessions with data architects, domain leads, and scientists to prioritize data ingestion and transformation activities
• Define story structure to comprise the requirements of the work to be done and the definition of done and the different types of tasks relevant for the domain to accomplish with their associated roles, documented in a Confluence page
• Endorse the role of agile scrum master for the RDH team: coach team members in self-management, organize high-value increments in sprints meeting the definition of done
• Identify and document potential data issues, including quality, normalization, duplication, completeness, or governance gaps, and share findings with the data domain and platform lead
• Work closely with data architects to define and document the data transformation pipeline architecture
• Support the data architect in defining and maintaining the data models used across regulatory use cases by reviewing proposed changes and evaluating their relevance towards new requirements
• Support the review phase led by the Data Domain Lead, verifying that the regulatory and business context is preserved across transformed datasets
• Validate that all data mappings and transformations meet regulatory compliance, data quality, and analytical readiness standards
• Collaborate with data scientists to define mapping logic for regulatory entities such as substances, studies, and documents
• Review the design of quality control pipelines, ensuring mapping accuracy and alignment with analytical expectations

• Bachelor’s degree in data analytics, computer science
• 5+ years of experience in data or business analysis, e.g., life sciences, agrochemical, or pharma domain
• Demonstrated expertise in data transformation pipelines, and data quality frameworks
• Hands-on experience with Databricks
• Familiarity with metadata management and data governance principles
• Strong analytical skills, with the ability to translate business requirements into technical deliverables
• Excellent communication and documentation skills, with experience collaborating across disciplines e.g. Data Scientists, Architects, Domain Leads, Platform Leads
• A collaborative and proactive approach, comfortable working in iterative, agile environments
• High attention to detail with strong problem-solving capabilities
• Self-motivated and adaptable, able to navigate ambiguity and evolving project priorities in a complex data environment
• Upper-intermediate English or higher

• Competitive compensation
• Remote or office work
• Flexible working hours
• Healthcare benefits: medical insurance and paid sick leave
• Continuous education, mentoring, and professional development programs
• A team with excellent tech expertise
• Certifications paid by the company