Staff Engineer, Data & Analytics

Kinaxis is a global leader in modern supply chain orchestration, and they are seeking a seasoned Staff Engineer, Data & Analytics to play a pivotal role in modernizing and advancing their data ecosystem. This role involves data integration, data engineering, and business intelligence to empower decision-making across the company.

Responsibilities:

• Transition legacy systems to a cloud-native, modern data stack leveraging tools such as Informatica, Airflow, Postgres and modern technologies like Snowflake, dbt, BigQuery, Looker, CI/CD, Git, Databricks, PowerBI, Datadog and Grafana
• Build innovative, scalable, and reliable data products that support Kinaxis’ strategic goals
• Build and maintain both batch and stream-based data pipelines for a wide variety of use cases, including the analysis of application and infrastructure logging data
• Build and maintain complex application to application data connectors
• Implement and oversee rigorous data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability
• Stay up to date on the latest technology trends and best practices as they relate to your role
• Partner with internal business stakeholders from different business units and cross-functional teams to design and deliver tailored data solutions
• Collaborate with peers specializing in FinOps, Data Architecture, Data Governance and Cloud Engineering to address diverse organizational needs
• Troubleshoot complex data engineering challenges with a focus on scalability and reliability
• Work collaboratively to prioritize tasks and deliver solutions in an agile environment
• Mentor and train junior engineers
• Distill complex projects into bite-sized, actionable stories
• Provide strategic oversight, lead large-scale initiatives. Help shape technical direction
• Develop robust data models and analytics solutions to drive actionable insights
• Develop and maintain complex BI models and visually appealing reports/dashboards for executive review
• Champion data-driven decision-making by ensuring stakeholders have access to meaningful, high-quality data
• Deliver compelling presentations and narratives to engage stakeholders and influence leadership
• Advocate for innovative data strategies that align with Kinaxis’ growth and innovation objectives

Requirements:

• 7+ years of hands-on experience in data engineering or analytics engineering, with a demonstrated history of owning and delivering production-grade data platforms at scale
• GCP expertise — deep, hands-on experience across core GCP services, including cloud-native storage architectures and compute
• Databricks & Lakehouse architecture — practical experience designing and operating lakehouse patterns at scale
• dbt — hands-on experience with data modeling and layered transformation patterns in a production environment
• Cloud-native orchestration & automation — experience with containerized or serverless services for pipeline scheduling and workflow automation
• Python & SQL — expert proficiency in both, with an emphasis on clean, maintainable, production-ready code
• Software engineering fundamentals — CI/CD, version control (Git), RESTful APIs, and a disciplined approach to testing and deployment
• Technical leadership — proven ability to mentor engineers, define technical standards, and translate ambiguous business requirements into well-scoped engineering solutions
• Cross-functional collaboration — experience working across business, architecture, and platform teams to deliver data solutions that drive real decisions
• Exposure to BI tooling such as Looker or Power BI, with an understanding of how end consumers interact with the data layer
• Certifications such as dbt Analytics Engineer, Google Cloud Professional Data Engineer, or Looker Certified Developer
• Experience with infrastructure-as-code tooling (Terraform, Ansible)
• FinOps awareness and a track record of implementing cloud cost optimizations
• Background in a SaaS environment