20 publicaciones de empleo destacadas en design assurance quality engineer (¡Están contratando!)

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Analytics Engineer

Capgemini Sogeti -
Aguascalientes, Ags.

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Información del empleo

Hace 6 horas

Cualificaciones

Modelado de datos
Procesamiento de señales digitales
DevOps
NumPy
Git
Google Cloud Platform
SQL
Pandas
Garantía de calidad
Mejora continua
Visualización de datos
Requisitos comerciales
Python

Descripción completa del empleo

Analytics Engineer

Your Role

As an Analytics Engineer, you will bridge the gap between data, technology, and business outcomes. You will design, develop, and optimize data-driven solutions using modern cloud platforms and machine learning technologies.

You will work closely with cross-functional teams and subject matter experts to understand complex technical domains and translate business requirements into scalable, high-quality analytical solutions. Your role will include developing and enhancing machine learning models, ensuring data quality, and delivering impactful insights that drive decision-making.

You will also contribute to continuous improvement through best practices in version control, quality assurance, and performance optimization, while working in agile environments.

Your Profile

Python programming (Strong coding background, including ML model updates)

Cloud platforms (Google Cloud Platform)
High-level machine learning knowledge
Machine Learning model integration and upgrading
Version Control (Git for collaborative development)
SQL querying
Pandas and NumPy
Quality Assurance knowledge
Translating business requirements to actionable technical steps
Collaborating closely with subject matter experts (SMEs) to gain a deep understanding of the technical and operational domain
Ability to work independently

Good-to-Have Skills

Data Modeling & ETL Processes

Agile / SCRUM Methodology (Experience delivering projects in Agile)
Oilfield Domain Knowledge (Terminology and business practices)
Dataiku
Performance Optimization & Monitoring (Profiling, scaling strategies)
Signal processing knowledge
Engineering background

Trainable Skills (COE Enablement)

CI/CD Pipelines & DevOps Tooling
Prognostics & Health Management Techniques (domain-specific analytics)

5. What you’ll love – Growth and Learning at Every Step

Access continuous learning through internal academies, certifications, and mentorship programs
Explore career mobility across roles, industries, and geographies
Gain hands-on experience with cutting-edge technologies in AI, cloud, and data
Develop your skills in a culture that fosters curiosity, innovation, and continuous improvement

About Capgemini

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.

At Capgemini Mexico, we aim to attract the best talent and are committed to creating a diverse and inclusive work environment, so there is no discrimination based on race, sex, sexual orientation, gender identity or expression, or any other characteristic of a person. All applications welcome and will be considered based on merit against the job and/or experience for the position.

Job Description

The role of a machine learning professional involves applying machine learning techniques and algorithms to solve complex problems, analyze data, and develop intelligent systems.

Job Description - Grade Specific

The role brings deep technical knowledge and expertise in machine learning to help clients or organizations navigate the complex landscape of AI. Plays a crucial role in providing designing solutions and ensuring successful implementation of machine learning projects to drive business impact. Also, assist in testing, deploying and monitoring models in production environments

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