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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.
Kong has different base pay ranges for different work locations within the United States, which allows us to pay employees competitively and consistently in different geographic markets. Compensation varies depending on a wide array of factors, including but not limited to specific candidate location, role, skill set and level of experience. Certain roles are eligible for additional rewards, including sales incentives depending on the terms of the applicable plan and role. Benefits may vary depending on location. The typical base pay range for this role in is CAD 123,025.00 - 147,677.50.
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.
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