Databricks Data Engineer / Developer (PL 866)

CanadaFull-timePosted 13 days ago
Description

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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