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.
MUST HAVE atleast 3+ years of hands-on Databricks development experience.
Required Qualifications
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 with Agentic frameworks and AI-assisted coding is a value add.
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.
Preferred Qualifications
Experience supporting large data platform initiatives.
Experience in significant data migration efforts.
Experience with Azure Data Services and Databricks Lakehouse architecture.
Experience with modern data engineering frameworks and best practices.
Exposure to AI, GenAI, Machine Learning, or advanced analytics initiatives.
Experience working in large enterprise or consulting environments.
Knowledge of data governance, metadata management, and data quality frameworks.
Technical Knowledge
Required
Databricks
ETL / ELT Development
Data Engineering
Data Integration
SQL
Python
Data Pipeline Development
Data Transformation
Data Warehousing Concepts
Agile Delivery
Preferred
Azure Data Factory
Delta Lake
Spark / PySpark
Azure Synapse
Data Lake Architecture
Cloud Data Platforms
Data Governance & Data Quality
CI/CD for Data Solutions
Key Skills & Experience
Databricks Development
Data Engineering
ETL/ELT Design & Development
Enterprise Data Platforms
Data Modernization
Data Migration
Data Warehousing
Cloud Data Platforms
SQL & Python Development
Data Quality & Validation
Agile Delivery
Stakeholder Collaboration
Ideal Candidate Profile
We are seeking a developer who:
✅ Has hands-on Databricks experience and can contribute immediately
✅ Understands enterprise data concepts and platform modernization initiatives
✅ Has strong ETL/ELT and data engineering experience
✅ Can partner effectively with architects, project managers, and business teams
✅ Is comfortable working in a fast-paced, highly visible enterprise transformation program
✅ Can help build a scalable lakehouse architecture supporting reporting, analytics, and future AI capabilities
Skills Required
- 3+ years of hands-on Databricks development experience
- 4+ years of overall Data Engineering, ETL, or Data Integration experience
- 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
- Experience supporting large data platform initiatives and migrations (e.g., HANA to modern platform)
- Experience with Azure Data Services, Delta Lake, Spark/PySpark, Azure Synapse, CI/CD for data solutions
- Knowledge of data governance, metadata management, and data quality frameworks
What We Do
Paralucent is a technology and marketing agency founded in 2003, based in Toronto, Canada. They specialize in delivering custom software applications, intelligent tools, and digital transformation services to help organizations simplify complex business processes. Their work spans financial services, telecommunications, and the public sector, focusing on driving measurable outcomes through technology and creative strategy.
