Senior Data Analyst / Engineer

Data Analyst / Engineer

manufacturing system owners

Key Responsibilities

• Analyze, validate, and

  authenticate data sets

  from manufacturing systems (SCADA, PLC, control systems).
• Identify gaps, missing values, and integrity issues in structured and semi-structured data.
• Implement

  data readiness and authentication protocols

  to ensure “fit-for-purpose” ingestion.
• Develop

  automation scripts, pipelines, and data preparation workflows

  to streamline readiness processes.
• Collaborate with CDL ingestion teams to fix and enrich data

  before and after ingestion

  into the CDL.
• Work with stakeholders to define

  data requirements per application

  , e.g., PI datasets.
• Provide technical support to

  parallel Trailblazer rollouts

  across multiple manufacturing sites.
• Create and maintain documentation for

  data readiness processes, authentication standards, and audit protocols

  .
• Contribute to building

  audit controls and monitoring frameworks

  for ongoing data integrity.

Required Skills & Experience

• 6–10 years’ experience as a

  Data Analyst / Engineer

  in manufacturing or industrial data environments.
• Strong understanding of

  SCADA, PLC, and manufacturing control systems data

  .
• Experience with

  data lakes (Azure/AWS/GCP)

  and relational database systems.
• Hands-on experience in

  data authentication, cleansing, validation, and readiness engineering

  .
• Proficiency in

  SQL, Python, or equivalent scripting

  for data processing/automation.
• Familiarity with

  PI (OSIsoft / Aveva)

  or other manufacturing data historians (trainable by Deen).
• Strong problem-solving skills for working with

  ambiguous or incomplete data sets

  .
• Ability to collaborate with both

  technical and functional (system owners, BSA)

  stakeholders.
• Excellent communication skills to bridge system data owners and engineering teams.

Desirable / Nice-to-Have

• Prior experience with

  data process automation

  in manufacturing systems.
• Exposure to

  audit/compliance controls

  in pharma or life sciences manufacturing.
• Working knowledge of

  data visualization and reporting tools

  .
• Familiarity with

  Agile/PI planning environments

  .