Software Engineering Technical Leader, Backend Data Engineer

Cisco
2 Locations$211k – $305kPosted 31 March 2026

Job Description

Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens. Meet the Team The SaaS Engineering organization within the Cisco Networking Group is committed to revolutionizing the deployment of generative AI applications. Our mission is to improve IT visibility and deliver comprehensive analytics for the AI infrastructure stack. By using ground-breaking technologies, we are developing next-generation SaaS-based controllers designed to efficiently manage Data Centers with AI/ML solutions like Nexus Hyperfabric. https://www.cisco.com/site/us/en/products/networking/data-center-networking/nexus-hyperfabric/hyperfabric-ai/index.html Your Impact You will shape the Hyperfabric data strategy and execute it. You will build and maintain in-product dashboards, APIs, and 3rd party system integrations, all while handling high-volume streaming data such as device telemetry, system alerts, etc. You are committed to designing and building robust and scalable systems that are easy to understand and maintain. Your contributions will directly impact how our customers interact with Hyperfabric by giving them visibility into their data centers’ performance, health, and more. You will innovate at the intersection of data AI. You will define and deploy our strategy to collect and stage our telemetry data. Leveraging this, you will build the AI workloads that transform this data into meaningful insights that we surface to our customers, including error detection, troubleshooting, performance tuning suggestions, etc. Responsibilities: Design and build forward-looking, performant, well-tested software with a specific focus on Go and Python. As a backend data engineer, you will focus on supporting both internal and external use cases. Design and build data pipelines that support Hyperfabric’s data APIs and notification streams, leveraging Druid, Kafka and more. Benchmark and tune these pipelines to support our workloads at high throughput and low latency and with fault tolerance. Deploy new functionality into production with rollout/rollback planning as well as monitoring and alerting. Collaborate with product managers, other software engineers, and QA through all stages of the software development lifecycle. Contribute to the team through technical design reviews, code reviews, and mentoring. Minimum Qualifications Bachelor’s 12 years of experience or Master’s 8 years of experience in software engineering or related field, with a focus on building cloud systems, including expertise in database, data lake and streaming systems. Experience building scalable data pipelines using Spark, Flink, or similar technology. Experience programming with two or more languages such as Go, Python, Bash, Java, C, C. Experience with AI-based code tools such as Codex, Claude Code, etc Preferred Qualifications Experience deploying or using Data Lakes/Warehouses, including storage, table format, and processing. Experience building and deploying AI-backed functionality, either customer-facing features or internal productivity tools. Expertise with Druid or another time-series analytics database. Expertise with Kafka or another streaming system Why Cisco? At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work a ... (truncated, view full listing at source)
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