Mexico City, Mexico
Open 6 months, first seen by us 185 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Build and maintain production-grade data pipelines with Azure Databricks, PySpark and ADF
Develop and manage the Bronze, Silver and Gold lakehouse pipeline architecture
Tune Delta Lake tables with Z-Ordering, liquid clustering, vacuuming and partitioning
Implement data governance, access controls and lineage tracking in Unity Catalog
Automate pipeline deployment with Terraform, Git and Azure DevOps
creating, deploying, and maintaining production-grade data pipelines utilizing Azure Databricks, PySpark, and Azure Data Factory (ADF)
developing and managing the comprehensive Lakehouse pipeline architecture across the Bronze, Silver, and Gold layers
advanced Delta Lake features such as Z-Ordering, liquid clustering, vacuuming, and partitioning techniques
Implement enterprise-level data governance frameworks, enforce access controls, and manage data lineage tracking utilizing Unity Catalog
managing and deploying cloud infrastructure using Terraform, Git, and Azure DevOps, automating the deployment of data pipelines
Proven experience in designing, developing, and optimizing scalable, cloud-based data pipelines is essential.
Proficiency in English, both spoken and written, is required for effective communication.
From the employer’s posting.
Open 6 monthsWe first saw this posting 185 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 185
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Tiger Analytics’s usual: its jobs come down by about day 68.
From 13,355 similar postings that came down, and 27 of Tiger Analytics’s. Coming down is not always a hire.
74 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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.
• 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.
• 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.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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
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Mexico City, Mexico
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