Azure Data Engineer (Databricks)
Contractor · Remote in Mexico (only)· Full-time · 3-6 month project (high chance of extension)

About the Role

We are seeking an experienced Azure Data Engineer / Senior Databricks Engineer to join a high-impact data engineering team focused on designing, developing, and optimizing modern cloud-based data platforms. In this role, you will build scalable data pipelines, implement Lakehouse architectures, and leverage Azure Databricks to deliver reliable, high-performance data solutions supporting enterprise analytics and business initiatives.

The ideal candidate has extensive experience with Azure Databricks, PySpark, Delta Lake, and modern data engineering best practices, along with a passion for building efficient and scalable data platforms.

Key Responsibilities

Design, develop, and optimize scalable batch and streaming data pipelines using Azure Databricks.
Build and maintain modern Lakehouse architectures following Medallion Architecture principles.
Develop robust ETL/ELT solutions using PySpark, Spark SQL, and Python.
Optimize Databricks workloads for performance, scalability, and cost efficiency.
Implement data quality, orchestration, and monitoring frameworks.
Collaborate with cross-functional teams to deliver enterprise-grade data solutions.
Participate in architecture discussions and contribute to cloud platform modernization initiatives.
Support CI/CD processes, deployments, testing, and production operations.
Ensure data governance, reliability, and adherence to engineering best practices.

Required Qualifications & Experience

Bachelor's degree in computer science, Information Technology, Engineering, or a related discipline, with 6-10 years of experience in Data Engineering, Application Development, System Integration, or Enterprise Data Warehouse projects.
Strong hands-on experience designing and implementing modern data platforms on Azure Databricks, leveraging Delta Lake, Delta Live Tables (DLT), and Medallion Architecture (Bronze, Silver, Gold) to build scalable and reliable data pipelines.
Proven expertise in developing and optimizing batch and streaming data pipelines using PySpark, Spark SQL, and Python, with a strong focus on performance tuning, scalability, and cost optimization.
Extensive experience in Databricks job performance optimization, including query tuning, partitioning strategies, data skew mitigation, caching, cluster sizing, workload optimization, and Spark execution plan analysis.
Strong proficiency in SQL programming and data modeling concepts, including relational, dimensional, and lakehouse data architectures.
Deep understanding of Delta Lake features such as ACID transactions, schema evolution, time travel, change data capture (CDC), and data quality enforcement.
Experience implementing data quality, monitoring, and orchestration frameworks using Delta Live Tables expectations, Databricks Workflows, and Azure-native services.
Strong exposure to the full Software Development Life Cycle (SDLC), including design, development, testing, CI/CD, deployment, and production support.
Solid understanding of Lakehouse architecture, cloud-based analytics platforms, data governance, and data engineering best practices.
Knowledge of real-time data processing, data integration patterns, and enterprise-scale data migration initiatives is a strong advantage.
Demonstrated ability to stay current with evolving cloud and big data technologies and contribute effectively to architecture discussions, technology strategy, and platform modernization initiatives.
Self-motivated, proactive, and capable of working independently in a fast-paced environment while collaborating with globally distributed teams.
Strong analytical, problem-solving, communication, and stakeholder management skills.

Why Join

Competitive compensation paid in USD.
100% Remote.
Paid Time Off: 12 PTO days per year.
Local Holidays: All official holidays in your country.
Birthday Off.
Career Growth.
Recognition Program.