la26.042 - Data Engineer
Tiger Analytics Inc.8 months ago
Remote, Mexico or Mexico City, MexicoMid Level
Responsibilities
- Create, deploy, and maintain production-grade data pipelines using Azure Databricks, PySpark, and Azure Data Factory.
- Develop and manage Lakehouse pipeline architecture across the Bronze, Silver, and Gold processing layers.
- Optimize Delta Lake using Z-Ordering, liquid clustering, vacuuming, and partitioning techniques.
- Manage and deploy cloud infrastructure with Terraform, Git, and Azure DevOps to automate data pipeline deployment.
- Implement data governance frameworks, access controls, and data lineage tracking using Unity Catalog.
- Monitor and optimize distributed Spark cluster performance, including cluster sizing, memory allocation, and execution plans.
- Collaborate on complex data engineering projects for global clients.
Requirements
- Over four years of experience with modern data stack technologies, particularly Azure Databricks and Medallion Architecture.
- Proven experience designing, developing, and optimizing scalable cloud-based data pipelines.
- Expertise with Azure Databricks, PySpark, Azure Data Factory, Delta Lake, Terraform, Git, Azure DevOps, and Unity Catalog.
- Experience optimizing distributed Spark clusters and their execution performance.
- Proficiency in spoken and written English.
- Availability to work from 8:00 AM to 5:00 PM PST.
Benefits
- 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.
- Remote and flexible working arrangements based in Mexico.
Tech Stack
Categories
Data Engineering
About Tiger Analytics Inc.
Tiger Analytics Inc. provides data and AI consulting services that deliver machine learning, analytics, and cloud data engineering solutions for large enterprises across industries, including life sciences. The company engages on strategy and implementation projects, from modern BI and data platforms to MLOps, helping Fortune 100 clients turn data into business outcomes. Founded in 2011 and headquartered in Santa Clara, it is privately held with operations across North America, Europe, and Asia-Pacific.