4 publicaciones de empleo destacadas de data engineer en miguel hidalgo, cdmx (¡Están contratando!)

la26.042 - Data Engineering Lead
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- Home Office (Desde casa)
- Azure
- DevOps
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- Español
- Azure
- DevOps
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NetPartners International —Ciudad de México, CDMX
- Español
- Azure
- DevOps
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- Trabajo híbrido
- SQL
- Python
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la26.042 - Data Engineering Lead

Tiger Analytics Inc. -
Ciudad de México, CDMX

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Información del empleo

Cualificaciones

Azure
DevOps
Spark
Git
Inglés

Descripción completa del empleo

Tiger Analytics is a leading AI and advanced analytics consulting firm dedicated to delivering impactful data-driven solutions to Fortune 100 companies worldwide. We specialize in helping organizations solve complex business challenges through innovative Data Engineering, Machine Learning, and AI techniques. We are currently seeking a highly skilled Data Engineering Lead to manage and lead complex data engineering projects, driving excellence and innovation in our delivery.

Requirements

We are seeking a highly experienced Data Engineer with over four years of expertise in modern data stack technologies, specifically focusing on Azure Databricks and the Medallion Architecture encompassing the Bronze, Silver, and Gold processing layers.
Proven experience in designing, developing, and optimizing scalable, cloud-based data pipelines is essential.
Pipeline Development & Orchestration: Responsible for creating, deploying, and maintaining production-grade data pipelines utilizing Azure Databricks, PySpark, and Azure Data Factory (ADF).
Medallion Framework Management: Accountable for developing and managing the comprehensive Lakehouse pipeline architecture across the Bronze, Silver, and Gold layers.
Delta Lake Optimization: Expertise in applying advanced Delta Lake features such as Z-Ordering, liquid clustering, vacuuming, and partitioning techniques to minimize query costs and improve read/write efficiency.
Infrastructure as Code & CI/CD: Collaborate in managing and deploying cloud infrastructure using Terraform, Git, and Azure DevOps, automating the deployment of data pipelines.
Data Governance & Security: Implement enterprise-level data governance frameworks, enforce access controls, and manage data lineage tracking utilizing Unity Catalog.
Performance Tuning: Monitor, analyze, and address performance bottlenecks in distributed Spark clusters by optimizing cluster sizing, memory allocation, and execution plans.
Proficiency in English, both spoken and written, is required for effective communication.
Working hours are from 8:00 AM to 5:00 PM PST.

Benefits

A collaborative and innovative work environment.
Opportunities to work on impactful projects with global clients.
Competitive salary and benefits tailored to mid to senior professionals.
Continuous learning and career development opportunities.
Flexible working arrangements based in Mexico.

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la26.042 - Data Engineering Lead

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