Location
Remote (Mexico)
Seniority
Middle · 4+ years exp
Overview
Company
Impact
Profile match
Tiger Analytics is a global data science and AI consulting firm headquartered in Silicon Valley, California. The company specializes in building customized data engineering, machine learning, and advanced analytics solutions for major enterprises across industries such as financial services, healthcare, retail, and manufacturing. With a global presence spanning the US, India, the UK, and Singapore, it helps Fortune 1000 companies transform complex data into actionable business value at scale.
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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