Databricks Data Engineer / Developer (PL 866)

Stack

Responsibilities

• ▹Design, develop and maintain data pipelines within the Enterprise Data Platform (EDP)
• ▹Build and optimize ETL/ELT processes
• ▹Apply an Agentic development approach
• ▹Develop scalable, reusable data solutions using Databricks and cloud-based technologies
• ▹Support migration and modernization from HANA environments
• ▹Collaborate with Data Architects on scalable data models
• ▹Develop data transformation logic and workflows
• ▹Ensure data quality, integrity, consistency and performance
• ▹Troubleshoot and resolve data-related issues and performance bottlenecks
• ▹Participate in code reviews, testing and deployment
• ▹Collaborate with business and analytics teams
• ▹Contribute to platform best practices and documentation

Requirements

• ▹3+ years of hands-on Databricks development experience
• ▹4+ years of overall Data Engineering, ETL or Data Integration experience
• ▹Strong experience building ETL/ELT data pipelines
• ▹Experience working with large, complex datasets
• ▹Experience developing data solutions on cloud-based platforms
• ▹Solid understanding of data warehousing, data lake and lakehouse concepts
• ▹Experience working in Agile delivery environments
• ▹Strong problem-solving and analytical skills
• ▹Excellent communication and collaboration abilities

Nice to have

• ▹Experience supporting large data platform initiatives
• ▹Experience in significant data migration efforts
• ▹Experience with Azure Data Services and Databricks Lakehouse architecture
• ▹Experience with AWS or Azure cloud platforms
• ▹Experience with modern data engineering frameworks and best practices
• ▹Exposure to AI, GenAI, Machine Learning or advanced analytics initiatives
• ▹Experience in large enterprise or consulting environments
• ▹Knowledge of data governance, metadata management and data quality frameworks
• ▹Experience with Agentic frameworks and AI-assisted coding

Soft skills

About the company

Paralucent's consulting client is modernizing its enterprise data landscape, building a next-generation Enterprise Data Platform (EDP) leveraging Databricks and modern cloud-based architecture.