Data Platform Engineer, Business Intelligence
About the role
Are you ready to power the World's connections? If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.
About The Role We are seeking a Data Platform Engineer to join our team. In this role, you will design, develop, and maintain scalable data pipelines and systems, leveraging modern data engineering tools and techniques. You will collaborate with cross-functional teams to ensure data is accessible, reliable, and optimized for analytics and decision-making processes.This position requires deep expertise in handling large-scale data systems, including Snowflake, Kafka, dbt, Airflow, and other modern ELT/Reverse ETL technologies.
What You'll Be Doing
- Design & Build Scalable Data Pipelines: Develop and maintain real-time and batch data pipelines using tools like Kafka, dbt, and Airflow/Snowpark.
- Data Modeling: Implement and optimize data models in Snowflake to support analytics, reporting, and downstream applications.
- Implement ELT Processes: Build efficient ELT pipelines for transforming raw data into structured, queryable formats.
- Reverse ETL Solutions: Enable operational analytics by implementing Reverse ETL workflows to sync processed data back into operational tools and platforms.
- Data Integration: Work with APIs, third-party tools, and custom integrations to ingest, process, and manage data flows across multiple systems.
- Automation: Leverage orchestration tools like Apache Airflow or Snowpark to automate workflows and improve operational efficiency.
- Collaboration: Partner with Data Scientists, Analysts, and Product teams to understand business requirements and deliver actionable data insights.
- Governance & Security: Implement and maintain data governance policies and ensure compliance with data security best practices.
What You'll Bring
- Technical Expertise: Experience with Snowflake: design, optimization, and query performance tuning. Hands-on experience with Apache Kafka for streaming data. Proficient in dbt for transforming data and creating reusable models. Expertise in Apache Airflow or similar orchestration tools. Knowledge of ELT and Reverse ETL principles.
- Programming: Strong proficiency in Python, Java and SQL.
- Data Systems: Experience working with modern data ecosystems, including cloud-based architectures (AWS, Azure, GCP).
- Data Modeling: Experience building and managing data warehouses and dimensional modeling.
- Problem-Solving: Strong analytical and debugging skills to tackle complex data engineering challenges.
- Collaboration: Excellent communication skills to collaborate with technical and non-technical stakeholders.
About Kong Kong Inc., a leading developer of cloud API technologies, is on a mission to enable companies around the world to become “API-first” and securely accelerate AI adoption. Kong helps organizations globally — from startups to Fortune 500 enterprises — unleash developer productivity, build securely, and accelerate time to market. For more information about Kong, please visit www.konghq.com or follow us on X @thekonginc.
Compensation Range: CA$123K - CA$147.7K
About Kong Inc.
Powering the API World. No AI without APIs.
Kong enables any company to become an API-first company. Kong’s unified cloud native API platform is easy to use and works in any environment — unleashing developer productivity, automating security, and boosting performance of APIs and microservices at scale.
Data Platform Engineer, Business Intelligence
About the role
Are you ready to power the World's connections? If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.
About The Role We are seeking a Data Platform Engineer to join our team. In this role, you will design, develop, and maintain scalable data pipelines and systems, leveraging modern data engineering tools and techniques. You will collaborate with cross-functional teams to ensure data is accessible, reliable, and optimized for analytics and decision-making processes.This position requires deep expertise in handling large-scale data systems, including Snowflake, Kafka, dbt, Airflow, and other modern ELT/Reverse ETL technologies.
What You'll Be Doing
- Design & Build Scalable Data Pipelines: Develop and maintain real-time and batch data pipelines using tools like Kafka, dbt, and Airflow/Snowpark.
- Data Modeling: Implement and optimize data models in Snowflake to support analytics, reporting, and downstream applications.
- Implement ELT Processes: Build efficient ELT pipelines for transforming raw data into structured, queryable formats.
- Reverse ETL Solutions: Enable operational analytics by implementing Reverse ETL workflows to sync processed data back into operational tools and platforms.
- Data Integration: Work with APIs, third-party tools, and custom integrations to ingest, process, and manage data flows across multiple systems.
- Automation: Leverage orchestration tools like Apache Airflow or Snowpark to automate workflows and improve operational efficiency.
- Collaboration: Partner with Data Scientists, Analysts, and Product teams to understand business requirements and deliver actionable data insights.
- Governance & Security: Implement and maintain data governance policies and ensure compliance with data security best practices.
What You'll Bring
- Technical Expertise: Experience with Snowflake: design, optimization, and query performance tuning. Hands-on experience with Apache Kafka for streaming data. Proficient in dbt for transforming data and creating reusable models. Expertise in Apache Airflow or similar orchestration tools. Knowledge of ELT and Reverse ETL principles.
- Programming: Strong proficiency in Python, Java and SQL.
- Data Systems: Experience working with modern data ecosystems, including cloud-based architectures (AWS, Azure, GCP).
- Data Modeling: Experience building and managing data warehouses and dimensional modeling.
- Problem-Solving: Strong analytical and debugging skills to tackle complex data engineering challenges.
- Collaboration: Excellent communication skills to collaborate with technical and non-technical stakeholders.
About Kong Kong Inc., a leading developer of cloud API technologies, is on a mission to enable companies around the world to become “API-first” and securely accelerate AI adoption. Kong helps organizations globally — from startups to Fortune 500 enterprises — unleash developer productivity, build securely, and accelerate time to market. For more information about Kong, please visit www.konghq.com or follow us on X @thekonginc.
Compensation Range: CA$123K - CA$147.7K
About Kong Inc.
Powering the API World. No AI without APIs.
Kong enables any company to become an API-first company. Kong’s unified cloud native API platform is easy to use and works in any environment — unleashing developer productivity, automating security, and boosting performance of APIs and microservices at scale.