Paralucent
Computer Software / SaaS
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Location: Remote within Canada
Client: Consulting Client
Contract Duration: 6 months contract
MUST HAVE atleast 3+ years of hands-on Databricks development experience.
Overview
Our consulting client is seeking a Databricks Data Engineer / Developer to support a strategic Enterprise Data Platform (EDP) transformation initiative. The organization is modernizing its enterprise data landscape and building a next-generation data platform leveraging Databricks and modern cloud-based architecture. This role will play a key part in designing, developing, and implementing scalable data solutions that support enterprise reporting, analytics, AI initiatives, and future data-driven capabilities.
The ideal candidate will possess strong data engineering expertise, hands-on Databricks development experience, and a solid understanding of ETL/ELT processes, data integration, and modern data architecture. This individual will work closely with data architects, project managers, analysts, and business stakeholders to deliver high-quality data solutions within a rapidly evolving environment.
Key Responsibilities
Design, develop, and maintain data pipelines within the Enterprise Data Platform (EDP).
Build and optimize ETL/ELT processes to support data ingestion, transformation, and integration requirements.
Make use of an Agentic approach to development and ensure that output matches development standards.
Develop scalable and reusable data solutions using Databricks and cloud-based data technologies.
Support migration and modernization activities from HANA environments to a modern data platform.
Collaborate with Data Architects to implement scalable data models and platform solutions.
Develop data transformation logic and workflows to support business and analytics requirements.
Ensure data quality, integrity, consistency, and performance across platform solutions.
Troubleshoot and resolve data-related issues, bottlenecks, and performance concerns.
Participate in code reviews, testing, deployment, and release activities.
Work closely with business and analytics teams to understand data requirements and deliver fit-for-purpose solutions.
Contribute to platform best practices, documentation, and continuous improvement initiatives.
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