Senior Big Data Engineer (9892)

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.

Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.

Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team.

Introduction: 

Extreme Networks is pushing the boundaries of technology, enabling progress and transformation through our innovative networking solutions. We are seeking a Data Engineer to join our Core Modelling Team. The successful candidate will play a pivotal role in our ambitious DT4N project, leveraging their expertise in handling network data and large-scale data systems. 

• Design, construct, install, test, and maintain data systems to support the DT4N project. 
• Handle the extraction and processing of network-specific data, including telemetry data and other network-related protocols. 
• Develop and optimize data pipelines, architectures, and data sets to support data transformation and structure. 
• Work with a range of big data technologies to design solutions for data problems. 
• Collaborate with the Core Modelling and Core Development teams to ensure efficient data delivery for modelling and development processes. 
• Communicate progress, challenges, and needs during the data engineering process to the Engineering Program Manager. 

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. 
• 5 years of proven experience in data engineering, where at least 2 were handling network-specific data like telemetry is a must.  
• Deep understanding of networks (protocols, architecture, operations and services) 
• Proficiency in tools and programming languages like Python, Pandas, Dask, and SQL. 
• Experience with big data technologies, such as Elasticsearch and other cloud-based solutions like AWS, Azure or Google Cloud. 
• Proficiency in using Docker and Kubernetes for scalable deployments. 
• Understanding of real-time data processing and the challenges associated with it. 
• Strong communication skills to effectively collaborate with team members and report to management. 

• Data Science knowledge/experience is a big asset. 
• Demonstrates a 'can-do' attitude, always seeking innovative solutions, and pushing boundaries. 
• Maintains a startup mindset, thriving in a dynamic, fast-paced environment, and contributing positively to team energy. 

Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.

We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on “protected categories,” Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.