Databricks Data Engineer / Developer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Databricks Data Engineer / Developer based in Canada.

This role offers the opportunity to contribute to a major enterprise data transformation initiative focused on building modern, scalable data platforms. The successful candidate will design and develop advanced data solutions that enable reporting, analytics, AI initiatives, and future data-driven capabilities. Working with architects, engineers, analysts, and business stakeholders, you will help shape a next-generation cloud-based data ecosystem. You will play a key role in developing reliable data pipelines, optimizing ETL/ELT processes, and improving data quality across enterprise systems. This position is ideal for a hands-on data professional who enjoys solving complex challenges and working with modern technologies. You will join a collaborative environment where innovation, continuous improvement, and technical excellence are highly valued.

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Accountabilities: The Databricks Data Engineer / Developer will support the design, development, and implementation of enterprise-grade data solutions. The role requires strong technical expertise, ownership of data engineering initiatives, and the ability to collaborate effectively across technical and business teams.

• Design, develop, and maintain scalable data pipelines within an enterprise data platform environment.

• Build and optimize ETL/ELT processes supporting data ingestion, transformation, integration, and analytics requirements.

• Develop reusable data solutions using Databricks and modern cloud-based data technologies.

• Apply AI-assisted and agentic development approaches to improve productivity while ensuring development standards are maintained.

• Support data platform modernization initiatives, including migration from legacy environments to modern architectures.

• Collaborate with data architects to implement scalable data models, lakehouse solutions, and platform improvements.

• Develop transformation logic and workflows that support business reporting and analytical needs.

• Ensure data quality, accuracy, consistency, security, and performance across platform solutions.

• Troubleshoot data issues, optimize performance, and resolve technical bottlenecks.

• Participate in code reviews, testing, deployment, and release activities.

• Partner with business teams, analysts, and project stakeholders to understand requirements and deliver effective data solutions.

• Contribute to documentation, engineering best practices, governance initiatives, and continuous improvement efforts.

Requirements:

The ideal candidate is an experienced data engineering professional with strong Databricks expertise and a proven ability to deliver enterprise-scale data solutions in cloud environments.

• 3+ years of hands-on Databricks development experience.

• 4+ years of experience in data engineering, ETL development, data integration, or related disciplines.

• Strong experience designing and developing ETL/ELT pipelines and transformation workflows.

• Proven ability to work with large and complex datasets.

• Experience developing solutions within cloud-based data platforms.

• Strong understanding of data warehousing, data lakes, and lakehouse architectures.

• Proficiency in SQL and Python development.

• Experience with enterprise data platforms, data modernization, and migration initiatives.

• Familiarity with Agile delivery methodologies and collaborative development environments.

• Strong analytical and problem-solving skills with the ability to troubleshoot complex data challenges.

• Excellent communication skills and the ability to collaborate with architects, technical teams, project managers, and business stakeholders.

• Experience with AI-assisted coding tools, agentic frameworks, or AI-driven development practices is considered an asset.

• Experience with Azure Data Services, Databricks Lakehouse architecture, Delta Lake, Spark/PySpark, Azure Synapse, or Azure Data Factory is preferred.

• Knowledge of data governance, metadata management, data quality frameworks, and CI/CD practices for data solutions is an advantage.

• Experience working in large enterprise or consulting environments is preferred.

Benefits:

• Fully remote opportunity within Canada.

• 6-month contract opportunity supporting a high-impact enterprise transformation initiative.

• Opportunity to work on modern data platform architecture and cloud-based technologies.

• Exposure to enterprise-scale analytics, AI, and future data-driven initiatives.

• Opportunity to collaborate with experienced data professionals, architects, and business stakeholders.

• Ability to contribute to innovative solutions using Databricks, lakehouse technologies, and modern engineering practices.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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