Senior Business Systems Analyst

Senior Business Systems Analyst (BSA)

requirements gathering, process mapping, and cross-functional collaboration

Key Responsibilities

• Partner with

  manufacturing system owners, Data lake teams, and business stakeholders

  to define

  data readiness requirements

  .
• Translate business needs into

  clear technical specifications

  for Data Analysts/Engineers.
• Document

  data authentication protocols, audit controls, and readiness standards

  .
• Conduct

  gap analysis

  to identify integrity issues, missing data, or inconsistencies impacting downstream systems.
• Support design of

  automated audit controls

  to ensure ongoing data quality and compliance.
• Work with Trailblazer rollout teams to align site-level data readiness solutions with deployment timelines.
• Develop and maintain

  process documentation, data flow maps, and user acceptance criteria

  .
• Act as the liaison between

  technical resources (data engineering teams)

  and

  business users (manufacturing, operations, QA)

  .
• Monitor progress, escalate risks, and ensure solutions meet both

  business and compliance requirements

  .

Required Skills & Experience

• 7–10 years’ experience as a

  Business Systems Analyst

  or related role in manufacturing / life sciences.
• Strong understanding of

  manufacturing systems data

  (SCADA, PLC, control systems) and downstream applications.
• Experience with

  data readiness, authentication, and audit protocols

  .
• Proven ability to

  translate complex data/technical concepts into business-friendly documentation

  .
• Familiarity with

  PI (OSIsoft / Aveva)

  or other manufacturing historians
• Excellent skills in

  requirements gathering, process documentation, and stakeholder management

  .
• Strong analytical mindset with the ability to

  work with ambiguous/incomplete data

  .
• Knowledge of

  regulatory and compliance considerations

  in pharma manufacturing data is a plus.

Desirable / Nice-to-Have

• Experience with

  Agile methodologies / PI planning

  .
• Prior work in

  data quality, governance, or audit frameworks

  .
• Exposure to

  data lakes, pipelines, and relational database ecosystems

  .
• Knowledge of

  pharma GxP data requirements

  .