Senior Manager, Data Engineering

Team: IT

Location: Canada

Commitment: Full-time

Workplace Type: remote

Accountabilities:

As a Senior Manager, Data Engineering, you will own the evolution of a scalable data ecosystem while leading engineering teams and partnering with business stakeholders. You will be responsible for improving platform reliability, enabling self-service analytics, and ensuring data products deliver measurable value across the organization.

• Lead, mentor, and grow a high-performing team of data engineers by establishing strong engineering practices, supporting career development, and fostering a culture of ownership and continuous learning.
• Own the reliability, quality, scalability, and operational excellence of core data platforms, including ingestion, transformation, orchestration, and serving layers.
• Establish strong data quality standards through lineage tracking, freshness monitoring, anomaly detection, observability practices, and reliable performance metrics.
• Drive the development of self-service analytics capabilities that reduce manual requests and empower teams to access trusted data independently.
• Manage platform efficiency by optimizing compute and storage costs while maintaining high reliability and performance standards.
• Partner with Data Science, Analytics, Product, Engineering, and business teams to define data models, semantic layers, governance practices, and data contracts.
• Promote engineering excellence through code reviews, testing strategies, CI/CD practices, incident response processes, and post-incident improvements.
• Encourage responsible adoption of AI-powered engineering tools to improve productivity, quality, and team effectiveness.
• Support strategic planning by translating business needs into scalable technical solutions and long-term platform improvements.

Requirements:

The ideal candidate is an experienced engineering leader with a strong background in data infrastructure, scalable systems, and team management. You bring technical depth, business awareness, and the ability to collaborate effectively across multiple functions.

• 8+ years of experience in data engineering, backend engineering, or data infrastructure roles, preferably within large-scale environments.
• 3+ years of experience managing engineering teams, including hiring, coaching, performance management, and team development.
• Strong expertise in building and operating large-scale batch and streaming data pipelines using technologies such as Spark, dbt, Airflow, or similar orchestration frameworks.
• Experience working with modern data platforms such as Databricks, Snowflake, BigQuery, or comparable lakehouse and warehouse technologies.
• Proven ability to own data reliability initiatives, including SLAs, observability, lineage, quality monitoring, and incident management.
• Strong understanding of data modeling principles, semantic layers, governance, privacy, and access-control practices.
• Ability to design scalable data products that support multiple stakeholders and business use cases.
• Excellent communication skills with the ability to align technical and non-technical teams around shared goals.
• Experience building self-service data platforms or reducing operational dependencies through automation and reusable solutions is preferred.
• Familiarity with AI-assisted engineering tools and experience applying AI responsibly within development workflows is a plus.
• Strong problem-solving abilities, adaptability, ownership mindset, and the ability to thrive in a fast-changing environment.

Benefits:

• Competitive compensation package based on experience and location.
• Salary range for eligible US locations: approximately $180,200 - $274,300 USD annually depending on compensation zone.
• Eligibility for company bonus programs and equity participation through Restricted Stock Units (RSUs).
• Flexible remote-first work environment designed around autonomy and collaboration.
• Opportunity to work with a global engineering organization building technology used at massive scale.
• Supportive culture focused on growth, innovation, and continuous learning.
• Opportunities to leverage modern technologies, including AI-powered tools, to improve engineering impact.
• Team gatherings, offsites, and intentional opportunities for in-person collaboration.
• Comprehensive employee benefits and wellness support.