Senior Data Engineer

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Location: Canada

Nexaminds is looking for a Senior Data Engineer to design, develop, and optimize scalable data solutions that support business-critical analytics and operational workloads. The ideal candidate has strong hands-on experience building modern data platforms, implementing data pipelines, and working with cloud-native technologies. This role is highly execution-focused, requiring strong technical expertise, ownership of data quality and performance, and the ability to collaborate effectively across engineering teams.

Qualifications we are looking for:

• 5–8 years of experience in data engineering, designing and delivering production-grade data solutions.
• Strong expertise in Databricks for data processing, transformation, and analytics workloads.
• Advanced Python and SQL programming skills with experience building scalable data pipelines.
• Strong understanding of data modeling, data profiling, and data quality best practices.
• Experience developing and maintaining Shell Scripts for automation and operational processes.
• Hands-on experience working with cloud platforms, preferably Azure.
• Experience with Azure Event Hub or similar event-streaming technologies.
• Experience implementing Infrastructure as Code (IaC) using Terraform.
• Familiarity with source control and artifact management tools such as GitHub and JFrog Artifactory.
• Strong troubleshooting, performance optimization, and problem-solving skills.
• Ability to collaborate effectively with cross-functional teams in an Agile environment.
• Advanced English communication skills are required.

Job duties:

• Design, develop, and maintain scalable data pipelines and data integration solutions using Databricks, Python, and SQL.
• Build and optimize data models to support analytical, reporting, and business intelligence requirements.
• Perform data profiling, validation, and quality assessments to ensure data accuracy and consistency.
• Develop automation scripts and operational tooling using Shell Scripting and Python.
• Implement and manage cloud-based data solutions within Azure environments.
• Build and maintain event-driven data processing solutions leveraging Azure Event Hub and related technologies.
• Develop and manage Infrastructure as Code using Terraform to support scalable and repeatable deployments.
• Collaborate with data architects, software engineers, and business stakeholders to define and implement data solutions.
• Manage source code repositories and deployment artifacts using GitHub and JFrog Artifactory.
• Monitor, troubleshoot, and optimize data platform performance, reliability, and scalability.
• Create and maintain technical documentation, operational procedures, and best practices for data engineering initiatives.