On-Site Data Analyst — Chemical Manufacturing Insights
Wood
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Benefits offered by this job
Job summary
Wood is seeking a Data Analyst to join its US Onshore Operations Americas business, supporting a chemical manufacturing facility in Washington, WV. The role focuses on transforming plant data into actionable insights for production, maintenance, reliability, and leadership teams through data models, dashboards, and applications.
The candidate will collaborate with operations, engineers, and digital stakeholders to improve data visibility and drive data-driven decisions.
Qualifications
- Bachelor's degree or equivalent in a data analytics, information systems, CS, engineering, or related field.
- Experience in manufacturing, chemical processing, or industrial environments.
- Experience creating Power BI reports, data modeling, Power Query, and DAX.
- Familiarity with Cognite Data Fusion or similar industrial data platforms.
- Experience supporting Power Apps solutions.
- Understanding relational databases and data integration concepts.
- Ability to translate operations needs into scalable technical solutions.
- Strong analytical, problem-solving, and troubleshooting skills.
Responsibilities
- Utilize Cognite Data Fusion to access, structure, manage, and maintain industrial datasets.
- Transform, cleanse, and validate data for quality and usability.
- Collaborate with operations, maintenance, reliability, and IT to define data requirements.
- Develop and maintain data models, documentation, and data flows.
- Design and maintain Power BI dashboards and reports for plant leadership.
- Create KPIs and visualizations focusing on production, reliability, and safety.
- Support Power Platform governance and app development.
- Ensure reports reflect current processes and metrics.
Skills
Education
Tools
Job description
Wood is seeking a Data Analyst to join its US Onshore Operations Americas business, supporting a chemical manufacturing facility in Washington, WV. The role focuses on transforming plant data into actionable insights for production, maintenance, reliability, and leadership teams through data models, dashboards, and applications.
The candidate will collaborate with operations, engineers, and digital stakeholders to improve data visibility and drive data-driven decisions.
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