Application Guide

How to Apply for Team Lead, Data Services and Infrastructure

at The AES Corporation

🏢 About The AES Corporation

AES is a global leader in sustainable energy, committed to innovation and decarbonization. Their Clean Energy division is at the forefront of solar, wind, and battery storage, making a tangible impact on the energy transition. Working here means contributing to a mission-driven company that values collaboration and cutting-edge technology.

About This Role

As Team Lead, Data Services and Infrastructure, you'll own the data backbone for AES Clean Energy's renewable fleet, ensuring reliable data pipelines and high-quality reporting. Your work directly enables analytics that optimize asset performance and drive business decisions, making you a key player in the clean energy revolution.

💡 A Day in the Life

You'll start by reviewing pipeline health dashboards and addressing any data quality alerts. Mid-morning, you might lead a stand-up with your team to prioritize tasks, then dive into code reviews or architecture discussions for a new data source. Afternoons often involve cross-functional meetings with analytics or operations teams to align on data requirements and deliver scalable solutions.

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Interview Prep

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🎯 Who The AES Corporation Is Looking For

  • Has 5+ years in data engineering with a focus on scalable pipelines and cloud platforms (GCP preferred, but Azure/AWS accepted).
  • Possesses strong leadership skills and experience mentoring or leading a team, not just individual contributor work.
  • Deeply understands data modeling, architecture, and governance, especially for operational and reporting systems.
  • Is passionate about renewable energy and can connect technical work to business impact in the clean energy sector.

📝 Tips for Applying to The AES Corporation

1

Tailor your resume to highlight leadership experience (e.g., team lead, mentoring) and specific projects involving data pipelines for renewable energy or similar IoT/operational data.

2

Emphasize your experience with GCP (BigQuery, Dataflow, etc.) as AES uses Google Cloud; if you have AWS/Azure, mention cross-platform adaptability.

3

Include metrics: e.g., 'Reduced pipeline latency by 30%' or 'Managed 10TB+ of data from 500+ solar assets' to show impact.

4

In your cover letter, connect your data engineering work to business outcomes like improved reporting or asset performance, not just technical details.

5

Research AES Clean Energy's CEDAR platform and mention how you'd contribute to its scalability and data quality.

✉️ What to Emphasize in Your Cover Letter

['Your leadership experience and ability to develop a team while maintaining hands-on technical involvement.', 'Specific examples of building scalable data pipelines for operational data (e.g., wind/solar/BESS assets).', 'Your proficiency with SQL and Python in a cloud environment, especially for data quality and reliability.', "Your alignment with AES's mission of sustainable energy and how your work supports data-driven decisions for clean energy."]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Read about AES Clean Energy's CEDAR platform and its role in analytics for renewable assets.
  • → Understand AES's sustainability goals and their recent projects in solar, wind, and battery storage.
  • → Look into AES's use of Google Cloud services (e.g., BigQuery, Dataflow, Pub/Sub) for data infrastructure.
  • → Check AES's company culture and values, especially around innovation and collaboration.

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you design a data pipeline to ingest real-time sensor data from thousands of solar inverters?
2 Describe a time you improved data quality or reliability across multiple systems. What metrics did you use?
3 How do you balance hands-on coding with team leadership? Give an example of mentoring a junior engineer.
4 What is your experience with data governance frameworks in a cloud environment? How do you ensure compliance?
5 Explain your approach to optimizing a slow ETL pipeline on GCP (or other cloud) for cost and performance.
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⚠️ Common Mistakes to Avoid

  • Don't focus solely on technical skills without demonstrating leadership or team development experience.
  • Avoid generic statements about 'clean energy'—show specific knowledge of solar, wind, or BESS data challenges.
  • Don't ignore data governance and quality; this role explicitly requires it, so be ready to discuss frameworks.

📅 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 The AES Corporation!

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