CINCO Engineering

We help Life Sciences protect their patients by managing the risks on their manufacturing processes.

Senior Data Analytics Specialist

Data EngineerData EngineerContractRemoteTeam 1-10Since 2004H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

7 days ago

Salary

Not specified

PythonSQLETLAWSAzureTableauRExcelData ModelingData GovernanceGMPComputer System ValidationPart 11FDA RegulationsData LineageData IntegrationData ArchitectureData TransformationData Curation

Job Description

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more.

Role Description

We are seeking a highly motivated and detail-oriented Senior Data Analytics Specialist to support the development and implementation of data repositories and analytics tools for pharmaceutical regulated environments operating under Good Manufacturing Practices (GMP). This role will focus on enabling data-driven insights across manufacturing and quality domains, ensuring data integrity, compliance, and effective use of analytics to support operational and quality decision-making.

  • Analyze business needs and requirements for data and analytics to support regulatory filings.
  • Identify, classify, and map data sources.
  • Build data lineage diagram from data source to analytics ready datasets.
  • Determine data curation requirements to help organize, clean, manage, and maintain data for reliable analytical use cases.
  • Provide support for technical activities such as building data integration, designing data architecture, and data transformation and processing.
  • Develop data governance standards to comply with company and industry best practices.
  • Lead development of key project documents such as user requirements, design specifications, and configuration specifications.
  • Lead development of test scenarios and scripts in partnership with business, technical, and validation team members.
  • Lead test execution according to test protocols.
  • Provide support for development of standard operating procedures and other documentation required to go-Live.
  • Monitor execution of testing and relay results to technical team to address issues.
  • Provide support for training business teams for Go-Live.
  • Development of training materials as needed.
  • Provide regular updates to project team.

Qualifications

  • Bachelor's Degree.
  • Minimum of 5-10 years of IT experience working in the role of business and technical analyst with a focus on data, business intelligence, and analytics projects.
  • Experience working in Biotech/Pharma (Regulated Industry).
  • Experience with developing requirements, design, and testing documents.
  • Hands-on experience with data analysis and reporting in support of Pharmaceutical GMP environment.
  • Experience with design and development and usage of data repository and analytics platforms.
  • Experience working with analytics (Python, R, Excel, Tableau, Spotfire, other reporting and analytics for manufacturing process industries).
  • Experience with database (SQL) and ETL development.
  • Experience with cloud environments (AWS, Azure).
  • Experience with usage of process analytic software is a plus (Aveva, Seeq).
  • Knowledge of System Support/System Administration, Communications, Project Management, Training, Computer System Validation, Business Requirements Documentation.
  • Demonstrated experience managing lifecycle documentation and validation in FDA-regulated environments.
  • Versed in FDA/Industry regulations and policies (Part 11, Computer System Validation).
  • Experience with system administration responsibilities.
  • Experience with helping lead data analysis and engineering projects.
  • Ability to work under tight timelines, communicate and work across teams in a collaborative manner, and work independently with minimal supervision.
  • GxP, Pharmaceutical Manufacturing and Quality Data (GMP data), Data analysis and reporting.
  • Understanding of GMP data sources across pharmaceutical manufacturing process and quality control testing environment sources such as Laboratory Management Information Systems, Quality Systems, Manufacturing Execution Systems, Data Historian, and other tools.
  • Understanding of data modeling tools.

Job Requirements

  • Bachelor's Degree.
  • Minimum of 5-10 years of IT experience working in the role of business and technical analyst with a focus on data, business intelligence, and analytics projects.
  • Experience working in Biotech/Pharma (Regulated Industry).
  • Experience with developing requirements, design, and testing documents.
  • Hands-on experience with data analysis and reporting in support of Pharmaceutical GMP environment.
  • Experience with design and development and usage of data repository and analytics platforms.
  • Experience working with analytics (Python, R, Excel, Tableau, Spotfire, other reporting and analytics for manufacturing process industries).
  • Experience with database (SQL) and ETL development.
  • Experience with cloud environments (AWS, Azure).
  • Experience with usage of process analytic software is a plus (Aveva, Seeq).
  • Knowledge of System Support/System Administration, Communications, Project Management, Training, Computer System Validation, Business Requirements Documentation.
  • Demonstrated experience managing lifecycle documentation and validation in FDA-regulated environments.
  • Versed in FDA/Industry regulations and policies (Part 11, Computer System Validation).
  • Experience with system administration responsibilities.
  • Experience with helping lead data analysis and engineering projects.
  • Ability to work under tight timelines, communicate and work across teams in a collaborative manner, and work independently with minimal supervision.
  • GxP, Pharmaceutical Manufacturing and Quality Data (GMP data), Data analysis and reporting.
  • Understanding of GMP data sources across pharmaceutical manufacturing process and quality control testing environment sources such as Laboratory Management Information Systems, Quality Systems, Manufacturing Execution Systems, Data Historian, and other tools.
  • Understanding of data modeling tools.

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