Product Development - Data Integrator

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Company: Cynet Systems

Location: New Brunswick, NJ 08901

Description:

Job Description:

Pay Range: $62hr - $65hr

Responsibilities:
  • Collect, streamline, and curate data from multiple structured and unstructured sources (data warehouses, spreadsheets, PDFs, slide decks, etc.).
  • Support identification of appropriate data sources for the project objectives, acquiring, integrating, and storing the data for the project, conducting appropriate analyses, and delivering results (in some instances visualizing results in platforms such as Tableau or Power BI).
  • pply data standards, ontologies, and metadata to facilitate data integration, automation, and analysis.
  • Ensure data quality, consistency, and completeness across different data sets.
  • Collaborate with business partners to identify data sources, understand data requirements and challenges, and provide data solutions.
  • Communicate and translate between business leaders and data engineers.
  • Support data Client, access, and sharing across the organization.
Qualifications:
  • Bachelor's degree or higher in a relevant field such as chemical engineering, life sciences, data science, or computer science.
  • 2+ Experience in a hands-on data integration and analytics role, preferably in the pharmaceutical industry or related domain.
  • Proven experience working with large datasets, data integration and transformation tools, statistical software packages and platforms (e.g., R, Python, advanced SQL, Domino, AWS, GitHub).
  • Strong proficiency in designing, developing, and maintaining interactive dashboards and reports in Tableau, Power BI, or other data visualization tools that provide insights to business users.
  • Excellent communication and interpersonal skills to work effectively with diverse stakeholders.
  • Strong problem-solving and analytical skills to handle complex data challenges.
  • Self-motivated and proactive to learn new skills and technologies.
  • Experience with major business/technical applications (e.g., SAP, LIMS) is preferred.
  • Familiarity with data standards, ontologies, and metadata for pharmaceutical CMC organizations is a significant plus.
  • Proficiency in predictive modelling, simulation, and optimization is beneficial.

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