3 publicaciones de empleo destacadas de python developer en ciudad de méxico, dif (¡Están contratando!)

Azure DevOps
Cognizant —Colonia Polanco, CDMX
- Tiempo completo
- Trabajo híbrido
- Azure
- DevOps
- SQL
4h
Principal Software Architect – Platform Integrations (with AI Focus)
Delinea —Ciudad de México, CDMX
- Tiempo completo
- Trabajo híbrido
- Azure
- Administración de personal
- Informática
- Seguro de vida
FBS MLOps Engineer Manager
Capgemini —Ciudad de México, CDMX
- $1 por año
- Tiempo completo
- Trabajo híbrido
- Administración de personal
- DevOps
- Inglés
- Vacaciones adicionales o permisos con goce de sueldo
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Programador Junior
Garrido Licona y Asociados , S.C —Benito Juárez, CDMX
Somos una Firma que se integra por profesionales con gran experiencia, que prestan sus servicios a empresas nacionales e internacionales.
$20,000 por mes
Postulación rápida
Programador
Industrias Goni —Industrial Vallejo, CDMX
Licenciatura o Ingeniería en Sistemas, Informática o afín (o experiencia equivalente). Experiencia en lenguajes como: [Java, Python, PHP, JavaScript, C#, etc.].
Desde $20,000 por mes
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Azure DevOps

Cognizant -
Colonia Polanco, CDMX

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Información del empleo

Tiempo completo
Hace 4 horas

Cualificaciones

Azure
Big data
DevOps
Spark
Cifrado
SQL
Mejora continua
Scala
Desarrollo de software
Seguridad
Requisitos comerciales
Python
PowerShell

Descripción completa del empleo

Job Summary
Serve as a senior developer specializing in Spark in Scala and Azure Synapse to design build and optimize large scale data engineering solutions that power analytics and digital products. Collaborate in a hybrid work model with cross functional teams to deliver secure reliable and observable pipelines while leveraging Azure DevOps and cloud native services to support business value including media domain scenarios.

Responsibilities
Design scalable batch and streaming data solutions using Spark in Scala and PySpark to support complex analytical workloads and reusable data products for enterprise stakeholders in a hybrid work environment.
Develop robust Synapse Pipelines that orchestrate ingestion transformation and publishing of structured and semi structured data from diverse sources into optimized analytical data stores.
Implement Structured Streaming jobs that process near real time data feeds to enable event driven analytics and timely business insights while maintaining reliability and consistency.
Configure and optimize Azure Synapse Spark Pool and Serverless SQL Pool to deliver cost efficient query performance and responsive data exploration capabilities for data consumers.
Write efficient SQL and Python code that adheres to coding standards while implementing reusable data transformation logic and ensuring maintainable modular solutions.
Use Azure CLI and Azure PowerShell to automate environment provisioning configuration changes and deployment tasks that improve consistency and reduce manual effort.
Set up and manage Azure Event Hub integrations that capture streaming events and route them into Synapse based processing pipelines with robust error handling and observability.
Configure Azure Monitor alerts metrics and logs that track pipeline health performance and failures to support proactive detection and quick resolution of production issues.
Implement secure secrets and credential management practices using Azure Key Vault to protect sensitive data while enabling safe automation and continuous delivery workflows.
Use Azure DevOps to design and maintain continuous integration and continuous delivery pipelines that enforce quality gates testing and automated deployment of data solutions.
Collaborate with architects data modelers and product partners to translate complex business requirements including media domain needs into scalable technical designs and implementation tasks.
Document data flows transformation logic operational runbooks and support guidelines that help teams understand operate and extend the implemented solutions over time.
Provide technical guidance and code reviews for peers by sharing best practices in Spark optimization Synapse development security and monitoring to uplift overall team capability.
Drive continuous improvement initiatives that enhance data reliability performance and developer productivity by introducing new patterns tools and process refinements aligned with organizational goals.

Qualifications
Possess eight to twelve years of professional experience in data engineering or software development with a primary focus on cloud based big data platforms and large scale analytics solutions.
Demonstrate deep hands on expertise in Spark in Scala and PySpark including performance tuning partitioning strategies job optimization and troubleshooting of distributed processing workloads.
Have strong practical experience building complex Synapse Pipelines and notebooks that integrate multiple Azure services and implement end to end data ingestion and transformation processes.
Exhibit proficiency with Azure Synapse Spark Pool and Serverless SQL Pool including workspace configuration resource management and query optimization for analytical use cases.
Show advanced skills in SQL and Python applied to data transformation data quality enforcement and analytical dataset preparation in large enterprise environments.
Bring practical experience with Azure CLI and Azure PowerShell scripting to automate operational tasks infrastructure configuration and deployment of repeatable environments.
Demonstrate familiarity with Azure Event Hub Structured Streaming and related technologies for implementing near real time and event driven data solutions.
Show working knowledge of Azure Monitor and related observability tools for setting up dashboards alerts and diagnostics that support production grade monitoring of pipelines.
Have solid experience with Azure DevOps including repositories pipelines and artifacts to implement continuous integration and continuous delivery for data projects.
Demonstrate strong understanding of security practices using Azure Key Vault role based access controls and encryption to protect data and credentials across environments.
Bring domain exposure in media or content centric industries where audience analytics streaming telemetry or digital engagement data are central to business decisions considered a plus.
Communicate clearly with cross functional teams manage work in a hybrid model and adapt to evolving priorities while maintaining focus on quality reliability and business outcomes.

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