About Kinaxis About Kinaxis Are you looking to join an innovative market-leading company where you can truly elevate your career? At Kinaxis we are serious about culture we are serious about technology we are serious about customers and we are serious about not taking ourselves too seriously. If you are looking to be part of an incredible growth story then we might just be the place for you! In 1984 we started out as a team of three engineers. Today we have grown to become a global organization with over 2000 employees around the world 6 global office and a best-in-class HQ in Ottawa Canada. As winners of several Top Employer awards globally we are proud to work with our customers and employees towards solving some of the biggest challenges facing supply chains today. Kinaxis is a global leader in modern supply chain orchestration powering complex global supply chains and supporting the people who manage them. Our powerful AI infused platform provides full transparency and visibility across end-to-end supply chains enabling our customers to make faster better decisions. We are trusted by renowned global brands to provide the agility and predictability needed to navigate today’s volatility and disruption. With more than 40000 users in over 100 countries we are expanding our team as we continue to innovate and revolutionize how we support our customers. About the team Location Ottawa and Toronto Canada - Hybrid (Preferred) Other Canadian locations - Remote About the team The Data & Analytics organization drives Kinaxis’ transformation into a data-driven organization by building trusted scalable and modern data capabilities that power analytics AI enablement customer-facing data products cloud intelligence and operational decision-making. The Data & Observability Platform team is responsible for the shared technical foundations that enable the broader Data & Analytics organization to deliver quickly and reliably. This includes ingestion frameworks Databricks and dbt platform enablement CI/CD and deployment patterns data and cloud observability modernization of legacy platforms and reusable standards that allow teams to safely build and operate data solutions at scale. This team partners closely with Data Architecture Analytics & AI Enablement Data Products & Integrations FinOps SRE Cloud Platform Engineering and business stakeholders across Kinaxis. About the role Vacancy Status This is an existing job vacancy What you will do We are seeking an experienced and hands-on engineering manager to lead the Data & Observability Platform team. This role will be responsible for building and operating the shared platform capabilities frameworks and observability foundations that support Kinaxis’ modern data ecosystem. You will lead a team focused on improving engineering velocity reducing delivery friction enabling consistent platform patterns and modernizing legacy data technologies. Your team will provide the foundation that allows other Data & Analytics teams to ingest transform monitor and operate data products and analytics solutions reliably. Success in this role will require strong technical leadership operational discipline stakeholder partnership and the ability to balance platform maturity with pragmatic delivery. You will help the organization move faster by creating reusable frameworks clear standards and reliable platform capabilities.Key responsibilities ### Leadership & Team Management Lead mentor and manage a team of data platform engineers and observability engineers. Build a high-performing engineering culture focused on reliability delivery speed automation and continuous improvement. Define team objectives delivery priorities and measurable outcomes aligned with Data & Analytics and Cloud Services goals. Coach team members on engineering practices operational ownership platform thinking and stakeholder partnership. Partner with other Data & Analytics leaders to ensure platform work is aligned to business and product priorities. Foster collaboration knowledge sharing and strong engineering discipline across the Data & Analytics organization. ### Data Platform & Engineering Foundations Own and evolve reusable ingestion frameworks templates and patterns for onboarding data into the modern data platform. Build and operate platform capabilities that support business analytics AI enablement product analytics customer-facing data products and integrations. Own Databricks and dbt platform enablement patterns including environment standards deployment workflows testing approaches and operational practices. Establish scalable patterns for service accounts permissions secrets logging monitoring and deployment automation. Partner with Data Architecture to ensure platform patterns align with enterprise standards security expectations and long-term architectural direction. Enable other teams to ingest and operate data safely using approved frameworks and standards. ### Observability Engineering Lead the delivery and ongoing operation of data observability and cloud observability platform capabilities for the Data & Analytics and the broader Cloud Services organization. Build and operate telemetry monitoring alerting and reliability patterns for data pipelines platform services and cloud-facing workloads. Support observability needs for all data products and cloud infrastructure hosting Kinaxis’ flagship Maestro offering. Establish standards for pipeline health data freshness failure handling operational dashboards and incident response. ### Modernization & Legacy Retirement Lead modernization of legacy data platforms pipelines and operational tooling into target-state GCP Databricks dbt and cloud-native patterns. Lead the migration and retirement strategy for legacy technologies such as Informatica Snowflake Airflow Postgres Grafana and Power BI Dataflows where applicable. Ensure migration work is delivered incrementally safely and with clear business continuity plans. Reduce technology fragmentation by creating repeatable patterns and minimizing one-off solutions. Partner with consuming teams to prioritize modernization work based on risk business value operational burden and renewal timelines. ### Platform Enablement & Engineering Velocity Improve developer experience for Data & Analytics teams through reusable frameworks CI/CD automation testing patterns documentation and self-service capabilities. Reduce dependency on manual cloud changes and external platform approvals by partnering with SRE and Cloud Platform Engineering on approved automation patterns. Establish practical standards for analytics-as-code infrastructure-as-code testing deployment and operational readiness. Identify bottlenecks in delivery flow and implement platform capabilities that reduce cycle time and rework. Promote a “thin vertical slice first harden and scale after” delivery mindset where appropriate. ### Stakeholder Engagement & Cross-Functional Partnership Act as the primary platform partner for Analytics & AI Enablement Data Products & Integrations Data Architecture SRE and Cloud Platform Engineering. Translate platform needs risks and dependencies into clear plans and trade-offs for technical and non-technical stakeholders. Communicate progress risks and modernization outcomes clearly to leadership. Support architecture review processes by ensuring new patterns are reviewed early and implemented consistently. Build strong relationships with teams that depend on the data platform for business analytics customer-facing insights integrations FinOps observability and AI enablement. Technologies we use Cloud & Platform Google Cloud Platform Microsoft Azure Databricks Data Engineering & Modeling Python SQL dbt Data Stores BigQuery Snowflake Postgres SQL Server Databricks BI & Analytics Consumers Power BI Looker Orchestration & CI/CD GitHub Actions Airflow CI/CD pipelines Observability Datadog Grafana Logstash cloud telemetry platforms Infrastructure Automation Terraform Ansible Development Tools Visual Studio Code Git Bitbucket/Stash Jira Confluence Integration Development GCP-native Python-based integration pattern What we are looking for Bachelor’s degree in Computer Science Engineering Information Systems or a related field. A Master’s degree is a plus. 5+ years of experience in data engineering platform engineering software engineering cloud engineering or related roles. 3+ years of experience leading or managing technical teams in a fast-paced technology environment. Strong experience with modern cloud data platforms preferably including Databricks dbt GCP BigQuery Snowflake or similar technologies. Strong understanding of data ingestion data modeling orchestration CI/CD data quality and production operations. Experience building reusable engineering frameworks platform patterns and developer enablement capabilities. Strong understanding of observability practices including monitoring alerting logging telemetry incident response and operational reliability. Experience modernizing or migrating legacy data platforms ETL tools pipelines or reporting infrastructure. Strong software engineering fundamentals including version control automated testing deployment automation and code review practices. Ability to partner effectively with architects product teams analytics teams SRE Cloud Platform Engineering and business stakeholders. Strong communication skills with the ability to explain technical trade-offs risks and delivery options to leadership. Experience in SaaS enterprise software or cloud-native environments is preferred. Experience with FinOps and/or cloud cost data is an asset. Experience with Python SQL dbt Databricks and GCP is strongly preferred. Success in this role looks like - Data & Analytics teams can onboard new data sources faster using approved ingestion frameworks. Databricks dbt and deployment patterns become more standardized and easier to use. Legacy platform retirement progresses against agreed timelines. Data and cloud observability capabilities improve operational reliability. Platform incidents are easier to detect diagnose and resolve. Delivery teams experience less friction from permissions environments CI/CD and platform dependencies. Architecture standards are implemented consistently without slowing delivery. Stakeholders see faster more reliable delivery of analytics AI data product and integration capabilities. #Manager Why join Kinaxis? Work With Impact Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day when we see store shelves stocked when medications are available for our loved ones and so much more.Work with Fortune 500 Brands Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Lockheed Martin Unilever P&G ExxonMobil Cisco and more. Social Responsibility at Kinaxis Our Diversity Equity and Inclusion Committee weighs in on hiring practices talent assessment training materials and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to a long-term net-zero operations strategy. We are involved in our communities and support causes where we can make the most impact. People matter at Kinaxis and here are some of the perks and benefits we offer which may vary by location and employee Flexible vacation and Kinaxis Days (company-wide days off) Flexible work options Physical and mental well-being programs Regularly scheduled virtual fitness classes Mentorship programs training and career development Recognition programs and referral rewards Hackathons For more information visit the Kinaxis website at www.kinaxis.com or the company’s blog at http//blog.kinaxis.com. Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates including those with specific needs or disabilities. If you require an accommodation please reach out to us at recruitmentprograms@kinaxis.com. This contact information is for accessibility requests only and cannot be used to inquire about the status of applications. Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description to identify candidates whose education experience and skills most closely match the requirements of the role. After the initial screening all subsequent decisions regarding your application including final selection are made by our human recruitment team. AI does not make any final hiring decisions.