Staff Software Engineer - Big Data (Gen AI)

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.

Position: Staff Software Engineer - Big Data (Gen AI)

Experience: 8 to 13 Years

Location: Remote/US

Job Responsibilities:

· Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation.

· Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation.

· Craft high-performance, Big Data Lakehouse architectures such as Hudi, Delta or Iceberg.

· Develop Big Data Platform to solve big data pipeline and processing.

· Mentor and develop other engineers on the team, establish technical direction and foster team culture.

· Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.

Basic Qualifications:

· Degree in mathematics/computer science or related discipline.

· 5+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments, and operations.

· 4+ years of experience in Spark/PySpark with an in-depth knowledge of its advanced features and libraries.

· 3+ years of experience in Data Lakehouse solution such as Hudi/Iceberg/Delta with an in-depth knowledge of its advanced features and libraries.

· 2+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).

· Proficient in Docker, Kubernetes, and modern CI/CD practices.

Preferred Qualifications:

· MS or PhD in Computer Science or equivalent experience in ML.

· Experience working with Big Data Infra such as AWS EMR.

· Experience with NoSQL and document databases.

· Proven ability to handle big data, optimize workflows, and improve system performance.

Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!

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.