Databricks Data Engineer

Join Deloitte in Tempe, AZ, onsite, as a Databricks Data Engineer. This role supports analytics and AI initiatives through the design, construction, and continual optimization of cloud-based data pipelines. The position offers a salary range of USD 86,700 to 170,900 per year and the opportunity to work closely with both client teams and Deloitte experts to deliver large-scale data transformation programs. You will gain hands-on experience with Databricks, Apache Spark, Python, and SQL while contributing to the modernization of enterprise data platforms and influencing how data supports decision making and innovation.

Responsibilities

• Create and sustain data pipelines and engineering solutions using Databricks, Apache Spark, Python, and SQL.
• Support the modernization of enterprise data platforms by implementing cloud-based ingestion, transformation, and storage patterns.
• Design and manage batch and streaming data workflows that underpin reporting, analytics, and AI use cases.
• Apply data architecture, integration, and modeling practices to improve data quality, scalability, and platform performance.
• Collaborate with client teams and Deloitte colleagues to troubleshoot issues, implement enhancements, and support delivery of large-scale data transformation programs.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, Mathematics, or Statistics.
• 3+ years of experience in data engineering, ETL development, or data platform engineering.
• 2+ years building data pipelines in Databricks using Apache Spark, Python, and SQL.
• Experience implementing data models, data integration patterns, and cloud-based data processing workflows.
• Experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
• Ability to travel approximately 50% on average.
• Limited immigration sponsorship may be available.

Technologies

• Databricks
• Apache Spark
• Python
• SQL
• AWS
• Azure
• GCP
• Delta Lake
• Databricks Workflows
• Unity Catalog
• Git

Preferred

• Experience with Delta Lake, Databricks Workflows, and Unity Catalog
• Experience using Git-based version control and CI/CD pipelines
• Experience supporting batch and streaming data workloads
• Experience with data warehousing, lakehouse architecture, and performance optimization
• Experience supporting analytics or machine learning data pipelines
• Experience working in consulting or client service delivery environments

Accommodation

Information for applicants with a need for accommodation: details available here