Application Guide

How to Apply for Product Manager - Customer Data and Gen AI

at Duke Energy

🏢 About Duke Energy

Duke Energy is a major utility company leading the clean energy transition with ambitious net-zero emissions goals, making it an ideal workplace for those passionate about sustainability. The company's focus on innovative technology solutions to modernize energy infrastructure offers unique opportunities to work on impactful projects at scale. Their commitment to both environmental responsibility and technological advancement creates a mission-driven environment where product work directly supports critical societal needs.

About This Role

This Product Manager role focuses specifically on customer data platforms and generative AI applications within Duke Energy's clean energy initiatives. You'll be responsible for developing data lakes at massive scale and implementing AI models that enhance customer experiences and operational efficiency. The position directly supports Duke Energy's strategic goals by leveraging data and AI to drive personalized energy solutions and accelerate the transition to clean energy.

💡 A Day in the Life

A typical day might involve morning stand-ups with data engineering and AI teams working on cloud infrastructure, followed by stakeholder meetings with business units to align product priorities with clean energy goals. You'd spend afternoons analyzing customer data insights, refining product roadmaps for AI applications, and preparing business cases for new data initiatives that support Duke Energy's net-zero transition.

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Interview Prep

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🎯 Who Duke Energy Is Looking For

  • Has 6+ years of experience specifically with cloud-based data lake implementation at enterprise scale (AWS, Azure, or GCP)
  • Demonstrates hands-on experience leading machine learning or AI model deployment in production environments, preferably with generative AI applications
  • Possesses strong stakeholder management skills with experience bridging technical teams, business leaders, and energy industry stakeholders
  • Shows understanding of both agile SDLC processes and energy/utility industry challenges related to customer data and clean energy initiatives

📝 Tips for Applying to Duke Energy

1

Highlight specific experience with cloud data platforms (AWS Redshift, Azure Synapse, Google BigQuery) and mention the scale of data lakes you've managed

2

Quantify your impact with AI/ML projects - include metrics like model accuracy improvements, deployment speed, or business outcomes achieved

3

Research Duke Energy's specific clean energy initiatives (like their net-zero roadmap) and connect your experience to how data/AI could support those goals

4

Emphasize experience working in regulated industries or with compliance-heavy data environments, as utilities have strict data governance requirements

5

Showcase your ability to translate technical AI/data concepts for non-technical energy industry stakeholders in your resume bullet points

✉️ What to Emphasize in Your Cover Letter

["Connect your data lake and AI experience directly to Duke Energy's clean energy transition and customer engagement challenges", 'Demonstrate understanding of how product management in utilities differs from tech companies, addressing compliance, safety, and reliability considerations', "Provide a specific example of how you've managed stakeholder relationships across technical and business teams in previous roles", "Explain how your experience with agile releases and SDLC processes would help accelerate Duke Energy's digital transformation initiatives"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Duke Energy's 'Clean Energy Action Plan' and specific net-zero emissions targets and timelines
  • → The company's recent digital transformation initiatives and any public information about their current data/AI capabilities
  • → Utility industry challenges related to customer data management, grid modernization, and renewable energy integration
  • → Regulatory environment affecting energy utilities' data practices and AI implementation

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you approach building a customer data platform that supports both current utility operations and future clean energy initiatives?
2 Describe your experience implementing AI models in production environments - what were the biggest challenges and how did you overcome them?
3 How would you prioritize product features when balancing regulatory requirements, customer needs, and business objectives in the utility sector?
4 What metrics would you establish to measure the success of generative AI applications in a customer-facing utility context?
5 How have you previously managed stakeholder relationships between data engineering teams, AI/ML specialists, and business leaders?
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⚠️ Common Mistakes to Avoid

  • Focusing only on tech industry experience without connecting it to energy/utility sector challenges and constraints
  • Using generic AI/ML terminology without demonstrating specific, hands-on experience with model deployment and scaling
  • Neglecting to address how you would handle the compliance and security requirements inherent in utility customer data management

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Duke Energy!

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