Senior Databricks Data Engineer - AI-Driven Pipelines

URUS Group; Oregon; Hybrid; USD 120,000 - 180,000; Full time

Job summary

URUS Group is seeking an experienced Data Engineer to design and maintain data integration and reporting solutions. You will work primarily in Databricks, building pipelines and datasets that feed reporting, analytics, and AI/ML workloads.

The role requires extending data warehousing capabilities, optimizing data flows, and collaborating with business users to define data requirements for complex reports and dashboards.

Qualifications

• Bachelor's Degree in Computer Science, Information Systems, or a related field.
• 7+ years of experience in data integration and reporting.
• Extensive experience with Databricks (Python, Spark, Delta Lake).
• Experience with data warehousing concepts and best practices.
• Strong proficiency with AI-assisted development tools.
• Strong proficiency in SQL Server (T-SQL, stored procedures, and functions).
• Experience with SSIS development and maintenance.
• Experience with SSRS report design and development.

Responsibilities

• Design, develop, and maintain ETL pipelines and processes on Databricks.
• Troubleshoot and resolve Databricks pipeline errors and performance issues.
• Troubleshoot and resolve SSIS package errors and performance issues.
• Migrate legacy systems (SSIS packages, SQL Server procs) to Databricks pipelines.
• Develop and maintain Databricks pipelines and datasets using Python, Spark and SQL.
• Collaborate with business users to understand data requirements for reporting needs.

Skills

Data integration

Data reporting

SQL

Azure cloud

Agile

Communication

Problem solving

Team collaboration

Education

Bachelor's degree in CS/IS

Tools

Databricks

Python

Spark

Delta Lake

SSIS

SSRS

SQL Server

Azure

Azure Data Factory

Job description

URUS Group is seeking an experienced Data Engineer to design and maintain data integration and reporting solutions. You will work primarily in Databricks, building pipelines and datasets that feed reporting, analytics, and AI/ML workloads.

The role requires extending data warehousing capabilities, optimizing data flows, and collaborating with business users to define data requirements for complex reports and dashboards.