Data Engineer / Developer

Paralucent

Databricks Data Engineer modernizing a Canadian enterprise data platform. Building ETL/ELT pipelines and lakehouse solutions supporting reporting, analytics, and AI initiatives.

Posted 8/5/2026contractRemote • 🇨🇦 CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing data pipelines using Databricks and cloud-based technologies, with a strong focus on ETL/ELT processes and data quality management. Proven ability to collaborate with cross-functional teams to deliver scalable data solutions that meet business and analytics requirements.

Highest-signal resume keywords

Databricks DevelopmentETL/ELT Data Pipeline BuildingCloud-Based Data SolutionsData Warehousing and Lakehouse ConceptsAgile Delivery Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData IntegrationData TransformationData Quality ManagementData MigrationData ModelingPerformance OptimizationTroubleshooting Data IssuesAI-Assisted CodingMetadata Management

Soft Skills

Problem-SolvingAnalytical SkillsCommunicationCollaboration

Tools & Technologies

Azure Data ServicesDatabricks LakehouseAgentic FrameworksAgile Methodologies

Industry Keywords

Enterprise Data PlatformData GovernanceContinuous ImprovementLarge DatasetsData Platform Initiatives

Tech Stack

Tools & technologies

AzureCloudETL

About the role

Key responsibilities & impact

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 meet development standards
Develop scalable and reusable data solutions with 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 transformation logic and workflows for business and analytics requirements
Ensure data quality, integrity, consistency, and performance
Troubleshoot data 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

Requirements

What you’ll need

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 Agentic frameworks and AI-assisted coding is a value add
Preferred: experience supporting large data platform initiatives
Preferred: experience in significant data migration efforts
Preferred: Azure Data Services and Databricks Lakehouse architecture experience
Preferred: modern data engineering frameworks and best practices
Preferred: exposure to AI, GenAI, Machine Learning, or advanced analytics initiatives
Preferred: large enterprise or consulting environment experience
Preferred: knowledge of data governance, metadata management, and data quality frameworks
Must be authorized to work in Canada

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Paralucent Website LinkedIn All 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. Data Engineer / Developer Job not on LinkedIn 🔥 1 hour ago 🇨🇦 Canada – Remote ⏳ Contract/Temporary 🟡 Mid-level 🟠 Senior 🚰 Data Engineer Azure Cloud ETL Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 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 meet development standards
Develop scalable and reusable data solutions with 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 transformation logic and workflows for business and analytics requirements
Ensure data quality, integrity, consistency, and performance
Troubleshoot data 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 🎯 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 Agentic frameworks and AI-assisted coding is a value add
Preferred: experience supporting large data platform initiatives
Preferred: experience in significant data migration efforts
Preferred: Azure Data Services and Databricks Lakehouse architecture experience
Preferred: modern data engineering frameworks and best practices
Preferred: exposure to AI, GenAI, Machine Learning, or advanced analytics initiatives
Preferred: large enterprise or consulting environment experience
Preferred: knowledge of data governance, metadata management, and data quality frameworks
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