Corporate Data Engineer II, Strategy

Radian Generation; Región Centro; Presencial; MXN 600.000 - 1.000.000; Jornada completa

Descripción de la vacante

Radian Generation is a global provider of technology-forward services supporting the renewable facilities lifecycle, including solar, wind, and energy storage. We empower developers, owners, and operators with data insights to drive decisions.

The role focuses on building ETL pipelines, dashboards, and AI-enabled data solutions, collaborating across functions to advance the Corporate Data Architecture and ensure data quality across the organization.

Formación

• University degree in Computer Science, Data Science, Mathematics or related field with 6+ years of experience.
• Certification in one or more data management technologies or methodologies.
• Expertise in Excel and SQL.
• Experience with at least one Business Intelligence tool set.
• Experience designing complex data models and hierarchies with structured/unstructured data.
• AI agent creation with understanding of AI use and pitfalls.
• Proven process improvement and automation skills.
• Understanding of data warehousing concepts/tools in AWS or Azure.
• Knowledge of data lake/lakehouse architecture and implementation.
• Strong problem-solving skills and passion for high-quality data management.

Responsabilidades

• Develop ETL pipelines for Sales, Finance, HR, and Radian Digital Software ensuring scalability and maintainability.
• Create interactive dashboards to provide data visibility and drive decision making.
• Create and maintain corporate data quality metrics.
• Improve data quality with data stewards via testing and validation.
• Collaborate with teams to automate processes using BI tools, SharePoint, and AI agents.
• Support AI growth by creating AI agents and instrumenting data sets.
• Collaborate with engineering to develop the next-gen Corporate Data Architecture.
• Port dashboards and data sets to the new Corporate Data Architecture.
• Continuously improve the Corporate Data Architecture and related ETLs, dashboards, apps.

Conocimientos

Excel

SQL

BI tools

Data modeling

AI concepts

Python

Ruby

Educación

Bachelor's degree in CS/DS/Math

Master's degree in CS/DS/Math

Herramientas

Domo

Tableau

PowerBI

Descripción del empleo

Radian Generation is a global provider of critical technology-forward services designed specifically to support the comprehensive lifecycle of renewable facilities—including solar, wind, and energy storage.

Who We Serve

Radian Generation’s wide range of commercial, technical, and compliance services provide developers, owners, and operators with critical insights into each aspect of their assets to make better-informed decisions.

Radian Generation is committed to supporting greater diversity in the renewable energy industry. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Role and Responsibilities

• Develop ETLs pipelines and processes for Sales, Finance, HR, and Radian Digital Software, ensuring extendibility, scalability and maintainability.
• Work with the user community to create interactive dashboards that provide visibility to data and help drive decision making.
• Create and maintain corporate data quality metrics.
• Work with system data stewards to continuously improve data quality and integrity through pressure testing and validation.
• Work with individual and cross-functional teams to create, optimize, and automate a wide range of processes. Optimization will include using a diverse tool set: automating via Business Intelligence tools, SharePoint workflows, creating AI agents, and using any other relevant tool sets to deliver solutions.
• Support the growth of AI throughout Radian by creating AI agents to solve problems, instrumenting data sets to use AI efficiently, and collecting and using AI metadata to provide insights and drive action.
• Collaborate with the engineering team to develop the next generation of the Corporate Data Architecture.
• Port existing corporate dashboards and data sets to the new Corporate Data Architecture.
• Continuously improve the Corporate Data Architecture and all the supporting ETLs, dashboards, apps, and related processes.

Required Qualification & Education

• University Degree in Computer Science, Data Science, Mathematics or a related field and 6+ years of applicable experience
• Certification in one or more data management technologies or methodologies
• Expertise in Excel, SQL
• Experience with at least one Business Intelligence tool set
• Experience designing and implementing complex data models and hierarchies, working with both structured and unstructured data
• AI Agent creation with accurate, repeatable results; understanding of AI use, benefits, and pitfalls
• Proven process improvement and automation skills
• Understanding of data warehousing concepts and tools in AWS or Azure
• Understanding of data lake / lakehouse architecture, design, and implementation
• Strong problem-solving skills and a passion for high quality data management

Required Software Knowledge

• 2+ yrs of Business Intelligence tool experience (Domo, Tableau, PowerBI)
• Proficiency with programming languages such as Python or Ruby

Preferred Experience

• Masters Degree in Computer Science, Data Science, Mathematics or a related field and 4+ years of applicable experience
• Experience unifying systems with similar but distinct approaches to data management
• Prior experience adopting newly acquired data products with related data into an existing data model
• Domo ETL, dashboard, and App creation
• Process optimization/development
• Certification in cloud computing and data management technologies in AWS (Sagemaker, Lambda, RDS, Redshift)
• Prior history working under Agile software development methods and tooling, such as Jira ticketing, Kanban process, etc.
• Lean Six Sigma certification / experience

Physical requirements

• Ability to use a computer for the duration of workday.