data engineer

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Location

This position will reside in Bend, Oregon. 

Acerca de Kollective 

Kollective Technology is a leader in enterprise collaboration observability and content delivery, helping organizations monitor, analyze, and optimize video and experiences across their networks. Our data engineering team plays a critical role within the product engineering organization, processing telemetry data to deliver actionable insights that demonstrate measurable value—from user experience monitoring to anomaly detection that help customers identify and resolve issues. 

About the Role 

We're looking for a Data Engineer to join our growing team of data engineers and scientists. In this role, you'll design and build scalable data pipelines, contribute to our streaming and batch processing infrastructure, and help shape our modern data architecture. You'll work closely with cross-functional partners in Product, Operations, and Engineering to deliver data solutions that directly impact customer experiences. Be prepared to work in a fast-paced and highly collaborative agile environment and help us deliver the next generation of features for the Kollective platform. 

 What You’ll Do 

• Build and maintain a scalable, secure, and cost-effective big data pipeline architecture 
• Build analytics tools for data mining, machine learning, and business intelligence use cases 
• Collaborate with backend software engineers to optimize data ingestion and schema for processing 
• Work with infrastructure engineers to build and monitor scalable infrastructure and keep our data secure 
• Work with product teams and business analysts to extract actionable insights from our data 
• Actively seek out and implement ways to improve our underlying processes and technologies 

What We Are Looking For 

Required 

• Bachelor's or Master's degree in Computer Science, Information Systems, or related technical field 
• At least 5 years of experience working with distributed systems, data engineering, or software architecture 
• Strong proficiency with Python or Java 
• Practical experience with containerization and orchestration technologies (e.g., Kubernetes, Docker) 
• Deep knowledge of cloud-native deployment architectures and experience with AWS, GCP, or Azure 
• Demonstrated expertise in performance tuning, monitoring, debugging, and optimizing distributed data processing pipelines 
• Exceptional problem-solving and troubleshooting skills in complex technical environments 

Preferred 

• Experience with a variety of open-source big data tools including Apache Flink, Apache Spark, Apache Kafka, Schema Registry, and Apache Iceberg 
• Experience with stream-processing systems and concepts 
• Experience with data lakehouse architectures and building ETL pipelines to create clean structured data models 
• Strong analytic skills related to working with unstructured datasets 

Please be prepared to provide 2-3 professional references as part of our application process