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Manager, Data Engineering (Analytics)

Brother Canada
Dollard-des-Ormeaux, CAN
Full Time
Manager
Hybrid
5 days ago
Data EngineeringAzureDatabricksAlteryxData GovernanceTeam Leadership
Free

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Role Overview

  • The Manager, Data Engineering is responsible for leading the development and optimization of the organization's data infrastructure to enable advanced analytics and data driven decision making.
  • This role oversees the design, integration, and governance of data pipelines and platforms, ensuring they are scalable, reliable, and aligned with business objectives.

Duties & Responsibilities Data Engineering

  • Lead the Development of Data Infrastructure: Be responsible for the design and implementation of scalable, high performing data pipelines and platforms.
  • Establish Governance Standards: Implement data governance policies, ensuring compliance, security, and data quality standards are consistently met.
  • Drive Innovation in Analytics Enablement: Partner with Data Scientists to design machine learning pipelines, enabling advanced analytics through optimized data preparation and feature engineering workflows.
  • Design and Oversee Data Integration Processes: Direct the integration of data from diverse systems using industry leading tools such as Databricks, Alteryx, and Azure.
  • Optimize Data Performance: Guide the optimization of data structures and workflows to enhance query performance, processing efficiency, and scalability.
  • Advance Organizational Capabilities: Stay abreast of emerging technologies, evaluate their relevance, and guide their adoption.
  • Champion Data Quality: Oversee the implementation of robust data validation and monitoring processes.
  • Support Organizational Strategy: Contribute to the design and implementation of analytics practices and data engineering frameworks.
  • Establish Standard Methodologies: Guide the standardization and adoption of standard processes in data engineering.

Team Management and Operations

  • Team Leadership and Development: Build and manage a high performing team by providing mentorship, coaching, and development opportunities.
  • Performance Management: Set clear objectives, manage workloads, provide regular feedback, and conduct annual performance reviews.
  • Competency Development: Support the development of technical and analytical skills within the team.
  • Coaching and Mentoring: Provide regular coaching to team members to guide their professional development.
  • Manage Operations: Supervise daily team operations, ensuring projects are completed on time and aligned with organizational goals.
  • Communication: Ensure effective communication within the team and with other departments.
  • Team Branding: Advocate for and communicate the team’s achievements to highlight their value.

Stakeholder Engagement and Continuous Improvement

  • Drive Continuous Improvement: Foster a culture of innovation by identifying and automating inefficient processes.
  • Stakeholder Engagement: Act as a liaison between the team, Analytics & Insights, IT, and business stakeholders.
  • Collaboration: Partner with data scientists, analysts, and business stakeholders to understand data needs and deliver tailored solutions.

Experience & Qualifications

  • Bachelor’s degree in computer science, Data Engineering, IT, or related field. Master’s degree or MBA preferred.
  • 8+ years of data engineering and analytics experience.
  • 3+ years managing teams and complex data engineering projects.
  • Experience with current data platforms (e.g., Azure, AWS, Snowflake) and ETL/ELT tools (e.g., Alteryx, Databricks).
  • Strong understanding of data governance, security, and compliance best practices.
  • Experience with designing data models, warehouses, and pipelines to support advanced analytics.
  • Experience with visualization tools (Tableau, Power BI).
  • Familiarity with machine learning frameworks and concepts preferred.

Additional Details For This Role

  • Hybrid Work Setting – Enjoy the flexibility of a hybrid model, with three days working remotely and two days in the office each week.

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