Sr. Data Engineer – Manufacturing Analytics - remote

Cognizant; Charleston (WV); Remote; USD 80,000 - 100,000; Full time

Job summary

A technology services company located in Charleston, West Virginia, is looking for an experienced candidate to develop analytical frameworks for potato fries production. The ideal candidate has a strong background in Python, experience with operational datasets, and an understanding of manufacturing processes. A Bachelor's degree in Computer Science and at least 10 years of experience in Python are required. This opportunity offers a dynamic work environment with significant stakeholder engagement.

Qualifications

• Minimum 10 years of experience in Python.
• Comfortable tackling ambiguous problems and structuring analytical approaches.

Responsibilities

• Develop and iterate on analytical frameworks for production stages.
• Collaborate with plant teams and insights teams to support data-driven decisions.
• Translate complex datasets into actionable insights.
• Build tools and dashboards for performance metrics and analytics.

Skills

Technical & Analytical Proficiency

Strong command of Python for data analysis and modeling

Experience with time-series and operational datasets

Familiarity with statistical methods and basic machine learning techniques

Data Visualization & Communication

Proficiency in visualization tools (Python libraries, Power BI)

Ability to present data findings clearly

Skilled in storytelling for diverse audiences

Manufacturing Domain Acumen

Problem Solving & Initiative

Communication & Stakeholder Engagement

Education

Bachelor's in Computer Science

Job description

Responsibilities

• Develop and iterate on analytical frameworks to evaluate capacity, throughput, and system constraints across potato fries production stages.

• Collaborate closely with plant teams, engineering, and insights teams to validate assumptions, refine models, and support data-driven decision-making.

• Translate complex datasets into actionable insights through impactful visualizations.

• Build tools and dashboards to monitor key performance metrics and enable self-service analytics.

Key Skills & Qualifications

1. Technical & Analytical Proficiency

2. Strong command of Python for data analysis and modeling.

3. Experience working with time-series and operational datasets.

4. Familiarity with statistical methods and basic machine learning techniques.

5. Data Visualization & Communication

6. Proficient in visualization tools such as Python libraries and Power BI.

7. Ability to present data findings in clear, concise, and actionable formats.

8. Skilled in storytelling through presentations for both technical and non-technical audiences.

9. Manufacturing Domain Acumen

10. Interest or experience in manufacturing, operations, or industrial systems (e.g., refrigeration, production lines, capacity planning).

11. Ability to understand plant operations and contextualize analysis within process flows and constraints.

12. Problem Solving & Initiative

13. Comfortable tackling ambiguous problems and structuring analytical approaches.

14. Experience designing or enhancing analytical frameworks from scratch.

15. Communication & Stakeholder Engagement

16. Strong written and verbal communication skills with a top-down approach.

17. Ability to collaborate across engineering, operations, and analytics teams.

18. Confident in presenting insights and recommendations to mid-to-senior level stakeholders.

Qualifications

Minimum 10 Years of experience in Python

Must have a Bachelors in Computer Science

Nice to Have

• Exposure to manufacturing data systems (e.g., PI System, SCADA, MES).

• Experience with simulation tools or modeling physical processes (e.g., heat transfer, fluid dynamics).

Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.