Staff Engineer, Data & Analytics

Kinaxis Inc.

1d•Hybrid

About The Position

The Data & Analytics team drives Kinaxis’ transformation into a data-driven organization. By designing and governing scalable, modern data ecosystems, we ensure reliable, high-quality, and accessible data that empowers decision-making across the company. Our expertise spans data integration, engineering, governance, business intelligence, and cloud cost optimization, enabling actionable insights, operational efficiency, and new business opportunities. We are seeking a seasoned Staff Engineer, Data & Analytics to play a pivotal role in modernizing and advancing our data ecosystem. This cross-functional role encompasses a wide range of responsibilities, including data integration, data engineering, data modeling, business intelligence and observability. As part of your journey, you will work closely with business stakeholders and collaborate with team members across the organization. You will modernize internal legacy systems into a cloud-native, modern data stack while also crafting innovative data products and enabling data-driven decision- making across Kinaxis.Your work will support the foundation of Kinaxis' strategic data initiatives by ensuring the quality and reliability of data pipelines that impact operational decision-making and enabling new revenues streams for the organization.Finally, your ability to engage stakeholders, craft compelling data stories, and influence leadership willbe critical to your success in this role.

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

Nice To Haves

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

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.