13 publicaciones de empleo destacadas de scientist , amazon music en loreto cdmx (¡Están contratando!)

AI Native Data Engineer
PALO IT —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Azure
- Administración de personal
- ERP systems
Postulación rápida
Senior Data Engineer
Salesforce —Ciudad de México, CDMX
- Tiempo completo
- Azure
- Salesforce
- Experiencia en bases de datos
Data Engineer
entropia AI —Ciudad de México, CDMX
- Trabajo híbrido
- Azure
- Java
- SQL
Postulación rápida
Data Engineer II, DASH Device Operations
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Informática
- Preparación de alimentos
- Java
Senior Full Stack Engineer – Lab Connect
Dotmatics —Ciudad de México, CDMX
- Microsoft Excel
- Inglés
- Experiencia en bases de datos
Cloud Data Analytics Engineer
Dotmatics —Ciudad de México, CDMX
- Microsoft Powerpoint
- Microsoft Excel
- Administración de personal
Production Finance, Originals, ROW Local Originals
Servicios Comerciales Amazon Mexico S. de R.L. de C.V. —Ciudad de México, CDMX
- Tiempo completo
- Microsoft Excel
- Microsoft Access
- Oracle
AI Presales
SDG Group —Ciudad de México, CDMX
- Trabajo híbrido
- Español
- Azure
- Doctorado
Postulación rápida
Quantity Surveyor
AECOM —Ciudad de México, CDMX
- Tiempo completo
- Sin título de educación superior
- Liderazgo
- Plan de adquisición de acciones empresariales
- Seguro dental
Java & API Application Support Engineer – AMS
Kyndryl —Ciudad de México, CDMX
- Tiempo completo
- Oracle
- Informática
- Microsoft Office
Senior Analyst, Demand Planning & Analytics
DoorDash Mexico —Ciudad de México, CDMX
- Microsoft Excel
- Inglés
- SQL
Postulación rápida
Staff Software Engineer - Data Processing & Execution Platform
Dotmatics —Ciudad de México, CDMX
- Microsoft Excel
- Administración de personal
- Informática
Senior Data Scientist, DTC
Levi Strauss & Co. —Centro (Área 1), CDMX
- Tiempo completo
- Doctorado
- Informática
- Maestría
Postulación rápida
6d

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entropia AI —Ciudad de México, CDMX
Buscamos un Data Engineer con conocimientos en diseño, integración y optimización de pipelines de datos en entornos de producción.
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AI Native Data Engineer

PALO IT -
Ciudad de México, CDMX

Postulación rápida

Información del empleo

Tiempo completo

Cualificaciones

Looker
Power BI
Azure
Administración de personal
Riesgos de préstamos
Spark
ERP systems
Inglés
Google Cloud Platform
Tableau
SQL
Análisis de riesgo
Apache
Kafka
Redshift
Python

Descripción completa del empleo

Who We Are

Building the AI-first frontier enterprise.

We are a global technology consultancy with a trademarked, AI-first approach—Gen-e2. It redefines how enterprises build digital products and transform their organizations with AI. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)
We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.
We are robust and resilient (100% independent, 0 debt, founded 2009)
We are AI-native professionals who invest in what we believe and work as a collective intelligence
We are positive, courageous and deliver at the leading edge.

Your Role

As a Data Engineer for a leading insurance company, you will play a key role in building a data-driven decision-making culture. You will design resilient and secure solutions that transform raw data into strategic insights for underwriting, risk management, fraud prevention, and customer experience.

Design, build, and maintain scalable and secure data pipelines in cloud environments (AWS, GCP, or Azure).
Integrate large volumes of structured and unstructured data from core insurance systems (such as policies, claims, CRM, ERP).
Automate data ingestion, transformation, and quality processes using tools such as Apache Spark, dbt, Kafka, and Airflow.
Build and maintain modern data lakes and warehouses (Snowflake, BigQuery, Redshift).
Implement data quality, lineage, and governance validations (Great Expectations, Deequ, OpenMetadata).
Ensure compliance with data regulations (GDPR, SOC2, etc.) and internal security policies.
Design optimized datasets to enable machine learning models, predictive analytics, and dashboards (Power BI, Looker, Tableau).
Collaborate with data scientists, architects, and business stakeholders to democratize access to trusted data.
Document data architectures, pipelines, transformation standards, and lineage.

Who You Are.

Experience with modern data processing frameworks: Spark, databricks, dbt, Kafka, Apache Beam.
Strong command of Python and advanced SQL.
Hands-on experience with Azure cloud platforms (Data Factory, Synapse).
Knowledge of modern Data Lake / Data Warehouse design (Snowflake, Redshift, BigQuery).
Familiarity with DataOps, testing, and CI/CD practices in data pipelines.
Experience with workflow orchestration systems such as Airflow or Dagster.

Understanding of data quality and governance frameworks: Great Expectations, Deequ, DataHub, OpenLineage.
Knowledge of streaming technologies: Kafka, Pub/Sub, Kinesis.
Upper-intermediate English level (B2 or higher) for global collaboration.

Nice to Have

Familiarity with event-driven architectures and microservices.
Previous experience in the financial or insurance sector.
Certifications such as Azure Data Engineer or Fabric Data Engineer.
Experience with MLOps solutions (Vertex AI, SageMaker, MLFlow).

AI-Native Engineering (Core Expectation)

Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:
Code scaffolding and refactoring
Code generation and optimisation
Test-cases and documentation generation
Build applications through AI-driven development practices, including:
AI-assisted debugging and troubleshooting
Intelligent code completion and pattern recognition
Automated documentation generation
Apply prompt engineering best practices for reliable, repeatable engineering outcomes.
Validate GenAI output (determinism checks, guardrails, fallback logic).

More About PALO IT

Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

What We Offer

Stimulating working environments
Unique career path
International mobility
Internal R&D projects (including Gen-e2)
Knowledge sharing
Personalized training via PALO IT Academy
Entrepreneurship & intrapreneurship

For more on our team culture and benefits, check out our careers page.

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scientist , amazon music empleos en loreto cdmx

AI Native Data Engineer

Senior Data Engineer

Data Engineer

Data Engineer II, DASH Device Operations

Senior Full Stack Engineer – Lab Connect

Cloud Data Analytics Engineer

Production Finance, Originals, ROW Local Originals

AI Presales

Quantity Surveyor

Java & API Application Support Engineer – AMS

Senior Analyst, Demand Planning & Analytics

Staff Software Engineer - Data Processing & Execution Platform

Senior Data Scientist, DTC

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Quiero recibir la alerta de empleo más reciente para scientist , amazon music en loreto cdmx

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Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

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Your Role

More About PALO IT Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

More About PALO IT

Our clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.