Used to be good - Recensione dipendente - Quantitative Data Analyst presso Xcel Energy

3,0
26 nov 2023
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

When I started during the pandemic, the company was very committed to making everyone feel part of a group. I felt seen and heard by the company. But the benefits are good.

Svantaggi

But in the past 6 months multiple layoffs including hearing "we aren't concerned about attrition" multiple times by executives means they want to trim as much as possible. So much bloat was put into third party consultants to build large scale projects while neglecting what goes into the employees has left the company with bare bones. Then we were told we had to go back to an office that is now partly empty and leaving groups isolated. There is FAR less diversity at the company as most of the people who were pushed out were not part of the traditional core type of person to work at Xcel. And now I just interact with the same person type just in different departments. Everyone seems to be overworked and now it seems that the contractors are in more pressure to prove that their products are worth it.

Esplora altre recensioni su Xcel Energy

5,0
15 giu 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Great, Lots of opportunity within,

Svantaggi

You have to drive to downtown Denver

5,0
18 mag 2026
Consiglia
Gradimento del CEO
Pronostico commerciale

Vantaggi

Standard methods, cloud infrastructure, and reliance on in house staff over contractors makes it very easy to implement safe, fast, consistent changes. You will be valued as a human and you will have a voice within this company. You can make a career here. Your coworkers and immediate leadership are all talented and intelligent individuals who actually know how to do the same work you are doing.

Svantaggi

AI rollout and unevenly applied hybrid work made things difficult for employees with disabilities and those that lived far from office who had traditionally worked remote or for tasks that do not lend themselves well to AI overhead

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