la26.042 - Data Engineering Lead

sJUKvzuwkZUks5P23HYp2PĀ· Data Engg
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šŸŒ RemotešŸ“ Mexico City, Mexico City, MexicošŸ“ TELECOMMUTE

About this role

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.

ā€¢ 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.

ā€¢ Proven experience in designing, developing, and optimizing scalable, cloud-based data pipelines is essential.

ā€¢ Pipeline Development & Orchestration: Responsible for creating, deploying, and maintaining production-grade data pipelines utilizing Azure Databricks, PySpark, and Azure Data Factory (ADF).

ā€¢ Medallion Framework Management: Accountable for developing and managing the comprehensive Lakehouse pipeline architecture across the Bronze, Silver, and Gold layers.

ā€¢ 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.

ā€¢ Infrastructure as Code & CI/CD: Collaborate in managing and deploying cloud infrastructure using Terraform, Git, and Azure DevOps, automating the deployment of data pipelines.

ā€¢ Data Governance & Security: Implement enterprise-level data governance frameworks, enforce access controls, and manage data lineage tracking utilizing Unity Catalog.

ā€¢ Performance Tuning: Monitor, analyze, and address performance bottlenecks in distributed Spark clusters by optimizing cluster sizing, memory allocation, and execution plans.

ā€¢ Proficiency in English, both spoken and written, is required for effective communication.

ā€¢ Working hours are from 8:00 AM to 5:00 PM PST.

  • 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.

Frequently Asked Questions

Is the salary disclosed for the la26.042 - Data Engineering Lead position at sJUKvzuwkZUks5P23HYp2P?
The salary for this la26.042 - Data Engineering Lead role at sJUKvzuwkZUks5P23HYp2P is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Is the la26.042 - Data Engineering Lead job at sJUKvzuwkZUks5P23HYp2P remote?
Yes, this la26.042 - Data Engineering Lead position at sJUKvzuwkZUks5P23HYp2P is remote, with team members based in Mexico City, Mexico City, Mexico, TELECOMMUTE. You can work from home or anywhere in the supported regions.
Which team or department does the la26.042 - Data Engineering Lead at sJUKvzuwkZUks5P23HYp2P belong to?
This la26.042 - Data Engineering Lead position is part of the Data Engg department at sJUKvzuwkZUks5P23HYp2P. See the full job description for more information about the team structure and responsibilities.
How do I apply for the la26.042 - Data Engineering Lead position at sJUKvzuwkZUks5P23HYp2P?
Click the "Apply Now" button on this page. You will be redirected to sJUKvzuwkZUks5P23HYp2P's official application portal hosted on workable where you can submit your application directly.
When was the la26.042 - Data Engineering Lead job at sJUKvzuwkZUks5P23HYp2P posted?
This la26.042 - Data Engineering Lead position at sJUKvzuwkZUks5P23HYp2P was posted on Mar 18, 2026. Apply as soon as possible ā€” early applications are often reviewed first.
la26.042 - Data Engineering Lead
sJUKvzuwkZUks5P23HYp2P
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