Data Engineer

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines and datasets in Databricks using Python, Spark, and SQL.
• Develop and support batch and streaming data architectures for reporting, analytics, and AI/ML workloads.
• Troubleshoot and optimize Databricks and existing data integration processes for performance, reliability, and data latency.
• Support and enhance existing SQL Server, SSIS, and SSRS solutions while contributing to ongoing platform modernization.
• Implement data quality checks, validation, cleansing, and data warehousing best practices across data pipelines and reporting environments.
• Integrate Databricks with enterprise applications, databases, and other data sources.
• Partner with business users, analysts, and IT teams to translate reporting and data needs into scalable technical solutions.
• Contribute to continuous improvement through emerging data engineering practices, AI-assisted development tools, documentation, and ongoing learning
  

Requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• Strong hands-on experience with Databricks, including Python, Spark, and Delta Lake.
• Strong SQL Server and data warehousing experience, including T-SQL.
• Experience with SSIS and SSRS.
• Experience with Microsoft Azure; Microsoft Fabric is a plus.
• Experience using AI-assisted development tools as part of the engineering workflow.
• Strong analytical, problem-solving, communication, and collaboration skills.