Description

You will design and implement scalable enterprise data architectures centered on Databricks and Azure, owning the technical strategy for data engineering, science, and analysis platforms.

Responsibilities

• Architect and document scalable data patterns, ETL frameworks, and governance policies using Databricks best practices.
• Define cloud data standards, DevOps practices, and CI/CD processes to ensure platform stability.
• Direct the strategic implementation of Databricks solutions to optimize performance and cost management.
• Implement security controls, audit solutions, and monitoring systems for enterprise-grade data platforms.
• Create technical documentation including data flow, conceptual, UML, and ER diagrams for stakeholders.

Required Skills

• 8+ years of experience in Software/Data Engineering or Data Applications Engineering.
• Expertise in implementing Databricks within new environments and on Azure.
• Proficiency in SQL, Python, Scala, or Java.
• Hands-on experience with Spark, Hadoop, and Kafka.
• Strong background in data modeling and ETL/ELT workloads on Azure Databricks.
• Experience with MPP databases and cloud infrastructure.
• Knowledge of data governance tools and BI tools such as Tableau or PowerBI.
• Experience with version control systems and CI/CD tools.

Preferred Skills

• Certifications in Databricks or cloud technologies (AWS or Azure).

Key Skills

Education

Bachelor's or master's degree in Computer Science, Information Technology