Software Technical Leader in Halifax

Remote: Based in Vancouver, BC or Toronto, ON, with office cadence aligned to local Cisco/Splunk policy.

Meet the Team

Cisco's Splunk Data Management organization owns the cloud-native services that help customers bring critical machine data into Splunk reliably, securely, and at scale. Our team builds and operates a hosted data ingestion platform used to connect cloud data sources, manage collection workflows, and deliver high-volume customer data into Splunk. The services are written primarily in Go, run on Kubernetes, and span distributed service architecture, secure data movement, customer onboarding, and operational tooling across many regions. Production ownership includes participation in the team's on-call rotation.

Your Impact

• Technical Leadership for Cloud Data Ingestion: Set technical direction for a hosted data ingestion platform, including service architecture, platform APIs, developer workflows, customer onboarding, and long-term platform evolution.
• Cloud-Native Platform Architecture: Design, build, and evolve Go-based cloud services and platform components on Kubernetes, balancing scale, cost, reliability, and operability.
• Data Integrity & Customer Trust: Drive designs that protect customer data through secure credential handling, reliable processing, failure recovery, and clear operational controls.
• Reliability, Scale & Operations: Own production quality for a multi-region ingestion platform through better observability, capacity planning, on-call participation, incident response, automated testing, and operational guardrails.
• Integration Ecosystem Acceleration: Make it faster and safer for engineering teams to add new data sources through reusable platform patterns, test frameworks, release processes, and readiness standards.
• Cross-Functional Influence: Partner with Product, cloud infrastructure, security, compliance, support, and field teams to turn customer and platform needs into crisp engineering priorities.
• Technical Mentorship: Mentor engineers across levels, lead design and code reviews, model high-quality technical decision-making, and grow the team's distributed systems and production engineering capability.
• Strategic Clarity & Communication: Synthesize platform tradeoffs, risks, and progress into clear communication for engineering leadership, product stakeholders, and partner teams.

Minimum Qualifications

• Bachelors + 8 years experience, professional software engineering, including ownership of production cloud services or distributed data systems.
• Programming: 3+ years of professional Go/Golang development experience is required, with a record of delivering maintainable production services.
• Scalable Cloud Architecture: Experience designing and building scalable distributed cloud-native architectures for SaaS or data platforms, with attention to throughput, latency, resilience, cost, and operability.
• Distributed Systems: Experience with distributed systems fundamentals such as concurrency, state management, leader election, scheduling, fault tolerance, retries, and eventual consistency.
• Cloud & Kubernetes: Hands-on experience building and operating containerized services on Kubernetes, including CI/CD, observability, security, on-call participation, and production support.

Preferred Qualifications

• Technical Ownership: Proven ability to drive architecture, execution, and technical decision-making in ambiguous, high-impact areas.
• Project Technical Leadership: Experience leading other engineers to deliver complex, high-impact projects across design, implementation, rollout, and production ownership.
• Splunk Platform Experience: Experience with Splunk Cloud, data onboarding, observability, security analytics, or related enterprise data platforms.
• Cloud Data Platform Experience: Experience with hosted integration platforms, API-based data collection, streaming or batch ingestion workflows, or extensible platform frameworks.
• Communication: Excellent written and verbal communication skills, including the ability to explain complex technical decisions to senior leaders and non-specialists.
• Data Ingestion Platforms: Experience with high-volume data ingestion, event processing, streaming systems, queues, or connector frameworks where correctness and reliability are critical.

Cisco may use AI Tools to review candidate-provided details—such as skills, experience, location, and education—to determine how closely candidates match job criteria. AI Tools are intended to guide and support the recruitment team in identifying and prioritizing candidates but are not used in isolation or without human judgment.

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.

We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.