Data Engineer

En AES, elevamos la calidad de vida en todo el mundo cambiando la forma en la que la energía funciona. Todos tienen un impacto cada día en nuestros equipos pequeños y globales. Postúlese aquí para iniciar una extraordinaria carrera hoy mismo. 

Our people are our energy and have transformed AES into the type of energy company that the world needs today and in the future. Coming from all walks of life, our people share a passion for improving lives by advancing the energy sector through innovation, collaboration and action.

We are working in an industry that requires new thinking and ways of working together to create solutions that are both economically and environmentally viable, not just one or the other.

We are looking for passionate people to join us in our mission to accelerate the future of energy.

At AES, we raise the quality of life around the world by changing the way energy works. Everyone makes an impact every day in our small, global teams. Apply here to start an extraordinary career today.

Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.

As part of its functions and responsibilities, and in coordination with the Data Services & Platform Lead, Data Science Team, Project Managers, and Business Relationship Leaders, it must also carry out the analysis, and studies and lead the work for the materialization of the projects related to its responsibilities and functions.

Responsibilities:

Supports data platform building, operation, and maintenance. Acquire datasets that align with business needs.

Ensure data is processed stably and reliably Develop algorithms to transform data into useful, actionable information.

Build, test, and maintain database pipeline architectures. Create new data validation methods and data analysis tools.

Ensure compliance with data governance and security policies. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Communications and Challenges:

The main internal contacts are Regional/Global digital relationship leaders, as well as all business units.

The main external contacts are: Service and outsourcing providers, IT manufacturers, and startups; as well as innovation and digital transformation organizations.

Job challenges are a deep understanding of artificial intelligence and machine learning, but also the skills to effectively communicate with multiple business units.

The position participates in integrating the organization towards a collaboration and innovation culture reflecting a business strategy leveraging the use of Data.

Qualifications and Experience:    

• Bachelor´s degree in IT/Digital Areas

Experience:

• 2 years minimum experience in Data Analysis / Engineering.
• Coding: Proficiency in coding languages is essential to this role. Common programming languages include SQL, NoSQL, Python, Java, R, and Scala.
• Relational and non-relational databases: Databases rank among the most common solutions for data storage. You should be familiar with both relational and non-relational databases, and how they work.
• ETL/ELT (extract, transform and load) systems: ETL/ELT tools include Talend, Prefect, Data Fusion, Xplenty, Stitch, Informatica, UiPath (RPA).
• Data storage: Not all types of data should be stored the same way, especially when it comes to big data. As you design data solutions, know when to use a data lake versus a data warehouse.
• Automation and scripting. Automation is a necessary part of working with big data simply because organizations can collect so much information. Experience writing scripts to automate repetitive tasks.
• Experience building and optimizing big data pipelines, architectures, and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Experience with enterprise data governance frameworks, data cataloging tools, and processes using the best practices in the market (Preferred).
• Google (GCP) BigQuery experience.
• Good Analytical and communication skills.
• Good communication in English (oral and written).
• Knowledge in:
  • General Information Technology
  • Big Data Analytics
  • Artificial Intelligence and Machine Learning
  • Data Visualizations
  • SQL and Non-SQL
  • GenAI
  • Google Cloud Platform (preferred), Azure, AWS  experience.
• Availability to travel.

Mejoramos la vida de más de 10+ millones de personas a través de la entrega segura  y confiable de energía. Uno de cada tres hogares se iluminan con nuestro trabajo.