Amazon

Solar Performance Engineer, Global Central Reliability Team (GCRT)

Milan, Italy Europe
SQL Python
Description
- Bachelor's degree in Electrical Engineering with data analytics experience, or equivalent practical experience
- Advanced understanding of control relays, inverters, and other balance of systems equipment.
- SQL and Python proficiency, including how SQL databases are structured and built.
- Experience with analytical tools such as Power BI and Tableau.
- Experience working with data acquisition systems including but not limited to PowerTrack, Powerdash, central SCADA systems for power and control automation.
- Fluency in English required.
- Degree in Engineering (any field) or a related field from an accredited university.
- Familiarity of analytical techniques.
- Experience of technical program management.
- Solar and Safety certifications and trainings.
- Knowledge of the solar market dynamics and opportunities (smart grid).
- Ability to review and manipulate data in Excel across multiple data sources.
- A plus is speaking other EU languages.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
An exciting opportunity in our endless pursuit of customer satisfaction through engineering excellence. The Global Central Reliability Maintenance Engineering (RME) team is seeking an exceptionally talented Solar Performance Engineer to work closely with the management of the operation and maintenance of the solar systems. If you have a passion for solar energy and new technologies, come join us as we shape the future of renewables for commercial and industrial scale.

The position will focus on the supervision of the solar systems located in EU and supporting the entire network managed by EU Solar RME, which may include non-EU locations (such as India, Australia and Japan). The position will require an individual strong in core principles of innovation, bias for action, ownership and insist on the highest standards.

The successful candidate will be a member of the Global RME team. Focusing on reliability and maintenance they will provide analytical feedback on optimizing solar and battery performance of assets. The ideal candidate is someone who is analytical, enjoys troubleshooting electrical systems related to solar and battery assets, and enjoys working in a fast-paced environment. You will be hybrid/remote out of Berlín offices. Constantly aiming for safety, optimum performance, efficiency, cost management, quality, customer satisfaction, and ultimately profitability within Amazon. They will work closely with technology owners, the central reliability team, regional solar asset managers, the operational sites, the maintenance vendors and other key stake holders that are part of the Solar Program of Amazon in EU.



Key job responsibilities
- Work with the current team as a subject matter expert to optimize solar and battery performance.
- Serve as an escalation point for critical or complex problem solving on both live assets and assets in commissioning.
- Establish means to identify underperformance and provide resolutions or next steps.
- Use field data to perform root cause analysis on system components experiencing underperformance or other issues in the field.
- Maintain data integrity and work with adjacent teams to repair broken data streams, manage current and historical operational data, and leverage data to inform and present on findings.
- Work with SQL database, or other third-party software to build and deliver automated custom reports.
- Develop new or improve existing tools and graphics that aid in the analytics and understanding of renewable energy performance in the fields of equipment tracking, degradation modeling, performance and revenue optimization, performance model to actual validation, regression analytics, field troubleshooting and root cause analysis, etc.
- Help automate and improve performance reporting capabilities.

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