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Lead Azure Data Engineer

Job Description - Lead Azure Data Engineer


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


As a Lead Azure Data Engineer, you will play a pivotal role in designing and delivering modern cloud-based data platforms that enable advanced analytics and AI-driven decision-making. Working within a collaborative, remote-first environment, you will lead the development of scalable Azure data solutions while mentoring engineering teams and driving technical excellence. This role combines strategic architecture, hands-on engineering, and leadership responsibilities, offering the opportunity to influence enterprise data strategies across multiple client engagements. If you are passionate about building high-performance data ecosystems and leveraging emerging AI technologies, this position provides an exciting opportunity to make a lasting impact.


Accountabilities



  • Lead the design, architecture, and implementation of enterprise-scale Azure data platforms using Microsoft Fabric, Azure SQL, Power BI, and modern Data Lakehouse architectures.

  • Partner with stakeholders to gather business requirements and translate them into scalable, secure, and high-performing data solutions.

  • Design and optimize ETL/ELT pipelines, semantic models, reporting layers, dashboards, and analytics solutions.

  • Drive migration initiatives from legacy data platforms to modern cloud-based environments while ensuring seamless data integration.

  • Establish governance standards for data quality, privacy, security, compliance, and long-term data retention.

  • Build AI-ready data pipelines that support advanced analytics, machine learning, and Generative AI use cases.

  • Mentor data engineers through technical leadership, code reviews, best practices, and knowledge sharing.

  • Collaborate with cross-functional engineering, product, and business teams to align data strategies with organizational objectives.

  • Monitor platform performance, troubleshoot complex data challenges, and continuously improve reporting and analytics capabilities.

  • Promote innovation by evaluating and implementing new cloud technologies, frameworks, and AI-assisted development practices.


Requirements



  • 7–10 years of experience in data engineering, business intelligence, or related data platform roles.

  • Strong expertise with the Microsoft Azure Data Stack, including Azure SQL, Microsoft Fabric, and Power BI.

  • Proven experience designing enterprise-scale cloud data platforms, Data Lakehouse architectures, dimensional models, and modern analytics solutions.

  • Advanced SQL skills and strong proficiency in Python for data engineering, automation, and ETL/ELT development.

  • Experience leading complex analytics or data engineering projects from design through deployment.

  • Ability to combine technical leadership with hands-on engineering contributions.

  • Strong understanding of data governance, security, privacy, multi-tenant architectures, and performance optimization.

  • Excellent communication skills with the ability to explain complex technical concepts to both technical and business stakeholders.

  • Experience with DBT, additional BI platforms, or Generative AI technologies is considered an asset.

  • Demonstrated commitment to engineering best practices, collaboration, and continuous learning.


Benefits



  • Remote-first work environment with flexible work arrangements.

  • Comprehensive medical and dental insurance (employee contributions apply).

  • Life insurance, AD&D coverage, and long-term disability insurance.

  • Paid vacation and paid time off.

  • 10 paid company holidays annually.

  • RRSP program with employer matching.

  • Opportunities to work on cutting-edge cloud, AI, and enterprise data initiatives.

  • Career growth through diverse projects, continuous learning, and global collaboration.

  • Wellness-focused culture with initiatives supporting physical and mental well-being.

  • Collaborative international team with exposure to global clients and technologies.


How 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!


 

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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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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