Databricks Data Engineer / Developer

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Paralucent

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

Paralucent is a company that operates at the intersection of technology and creativity, focusing on driving automation and fusing intelligence to empower productivity. They aim to simplify documentation and enhance business processes through innovative technology solutions. Paralucent offers its expertise to clients seeking to integrate advanced AI solutions into their operations, helping them to optimize their workflows and increase efficiency.

📋 Description

• Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP) • Build and optimize ETL/ELT processes for data ingestion, transformation, and integration • Use an Agentic approach to development and ensure outputs match development standards • Develop scalable and reusable data solutions using Databricks and cloud-based data technologies • Support migration and modernization from HANA environments to a modern data platform • Collaborate with Data Architects on scalable data models and platform solutions • Develop data transformation logic and workflows for business and analytics requirements • Ensure data quality, integrity, consistency, and performance • Troubleshoot data-related issues, bottlenecks, and performance concerns • Participate in code reviews, testing, deployment, and release activities • Work with business and analytics teams to understand requirements and deliver fit-for-purpose solutions • Contribute to platform best practices, documentation, and continuous improvement initiatives

🎯 Requirements

• At least 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 and transformation processes • Proven experience working with large and complex datasets • Experience developing data solutions within 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 • Experience with Databricks, ETL/ELT development, data engineering, data integration, SQL, Python, data pipeline development, data transformation, and data warehousing concepts • Experience with Agentic frameworks and AI-assisted coding is a value add • Preferred: experience supporting large data platform initiatives, significant data migrations, Azure Data Services, Databricks Lakehouse architecture, modern data engineering frameworks, AI/GenAI/Machine Learning/advanced analytics, enterprise or consulting environments, data governance, metadata management, and data quality frameworks • Preferred technical knowledge: Azure Data Factory, Delta Lake, Spark/PySpark, Azure Synapse, data lake architecture, cloud data platforms, data governance and data quality, and CI/CD for data solutions • Applicants must state their work authorization in Canada