Manager, Data Engineering

Company Overview

Kinaxis is a pioneering global supply chain orchestration leader, dedicated to helping customers manage complex international supply chains through a powerful AI-driven platform. Since its founding in 1984 by three engineers, it has expanded to a worldwide organization with over 2,000 employees and multiple offices, including a central headquarters in Ottawa, Canada. Kinaxis supports over 40,000 users across more than 100 countries, partnering with renowned global brands to deliver agility and predictability in today’s volatile markets.

Location

• Preferred hybrid presence in Ottawa and Toronto, Canada
• Remote work available for other Canadian locations

Team Overview

The Data & Analytics division spearheads Kinaxis’ journey toward becoming a data-centric organization. It builds trusted, scalable modern data capabilities serving analytics, AI, customer-facing data products, cloud intelligence, and operational decisions. The Data & Observability Platform team manages foundational shared technologies like ingestion frameworks, Databricks and dbt enablement, CI/CD pipelines, observability and monitoring tools, and the modernization of legacy platforms — enabling safe, scalable data solutions.

Role Summary

This role requires a practical, leadership-oriented engineering manager to guide the Data & Observability Platform team. Responsibilities include developing and running shared platform capabilities and observability foundations that empower Kinaxis’ data ecosystem. The manager will enhance engineering speed and quality by creating reusable frameworks and standards, reducing delivery obstacles, and modernizing outdated technologies.

Primary Responsibilities

• Lead and mentor a team of data platform and observability engineers, fostering a culture centered on reliability, automation, and continuous improvement.
• Define objectives, delivery priorities, and measurable outcomes aligned to organizational Data & Analytics goals.
• Develop reusable ingestion frameworks, deployment templates, and platform enablement patterns for Databricks, dbt, and associated cloud data tools.
• Manage observability engineering efforts including monitoring, alerting, logging, telemetry, and incident response to sustain operational reliability.
• Drive the migration and modernization of legacy data platforms and tools towards cloud-native solutions on GCP, Databricks, and modern architectures.
• Improve developer experience by implementing CI/CD automation, testing approaches, documentation, and self-service capabilities.
• Collaborate cross-functionally with leaders in Data Architecture, AI Enablement, SRE, Cloud Engineering, and business stakeholders to align platform work with overarching priorities.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related discipline (Master’s degree preferred).
• Minimum of 5 years in data, platform, software, or cloud engineering roles.
• At least 3 years’ experience managing technical teams in dynamic technology settings.
• Hands-on expertise with modern cloud data platforms such as Databricks, dbt, Google Cloud Platform, BigQuery, Snowflake.
• In-depth knowledge of data ingestion, modeling, orchestration, CI/CD pipelines, data quality, and production operations.
• Proven ability to construct reusable engineering frameworks and developer enablement tools.
• Strong grasp of observability principles, including monitoring, alerting, logging, telemetry, and incident management.
• Experience leading migration or modernization of legacy ETL platforms, data infrastructures, or reporting ecosystems.
• Solid software engineering foundations: version control, automated testing, deployment automation, code reviews.
• Excellent communication skills facilitating collaboration with architects, product teams, analytics teams, SREs, cloud engineers, and business partners.
• Background in SaaS, enterprise software, or cloud-native environments is desirable.
• Additional familiarity with FinOps or cloud cost management is a bonus.
• Preferred skills: Python, SQL, dbt, Databricks, and Google Cloud Platform.

Success Indicators

• Accelerated onboarding of new data sources using standardized ingestion frameworks.
• Standardization and simplification of Databricks, dbt, and deployment workflows.
• Effective progress toward retiring legacy platforms within agreed timelines.
• Enhanced operational reliability enabled by improved data and cloud observability capabilities.
• Quicker detection and resolution of platform incidents.
• Reduced friction in delivery workflows related to permissions, environments, CI/CD, and dependencies.
• Consistent enforcement of architectural standards without compromising delivery speed.
• Faster, more dependable delivery of analytics, AI, data products, and integrations witnessed by stakeholders.

Technologies Utilized

• Cloud platforms: Google Cloud Platform, Microsoft Azure, Databricks
• Data engineering: Python, SQL, dbt
• Data stores: BigQuery, Snowflake, Postgres, SQL Server, Databricks
• BI & analytics tools: Power BI, Looker
• Orchestration and CI/CD: GitHub Actions, Airflow, various CI/CD pipelines
• Observability tools: Datadog, Grafana, Logstash, cloud telemetry
• Infrastructure automation: Terraform, Ansible
• Development tools: Visual Studio Code, Git, Bitbucket/Stash, Jira, Confluence
• Integration approach: GCP-native Python-based integration patterns

Company Culture and Benefits

Kinaxis emphasizes culture, technology, innovation, and customer focus balanced with a lighthearted environment. The company prioritizes social responsibility including diversity, equity, inclusion efforts, unconscious bias training, and sustainability via a net-zero operations goal. Kinaxis actively contributes to community causes.

Employee perks (varies by location) include flexible vacation and company-wide days off, flexible remote work options, mental and physical wellness programs, virtual fitness classes, mentorship programs, ongoing career development, recognition programs, referral rewards, and hackathons.

Accommodation and Inclusion

The recruitment process is inclusive and accessible. Kinaxis offers accommodations for candidates with specific needs or disabilities upon request to ensure fairness. Contacts for accommodation requests are provided exclusively for accessibility purposes.