Engineering Product Manager

The application window is expected to close on: 09/28/2026

Meet the Team

Splunk, a Cisco company, helps the world’s most complex organizations turn machine data into action. The Data Management team builds the foundational products that help customers collect, process, govern, and optimize data across hybrid, multi-cloud, and edge environments.

Our work powers security, observability, AI, compliance, cost optimization, and enterprise analytics use cases at global scale. We help customers make high-volume data usable, trustworthy, and valuable before it reaches the systems and teams that depend on it.

We are reimagining data management with automation-first and intelligence-assisted experiences that make sophisticated workflows easier to build, operate, and trust. Joining this team means working on platform capabilities with reach across Splunk, Cisco, and some of the world’s largest enterprises.

Your Impact

We're looking for a Senior Product Manager to lead the next evolution of Splunk's Data Pipeline Building experience. This is a high-impact role at the heart of Splunk's transformation into Cisco's foundational Data Fabric, where you'll define how customers transform raw data into actionable, well-governed streams from edge to cloud.

You'll shape the API and UI building blocks that help technical users create powerful, scalable, and intuitive pipelines, whether they are filtering noisy telemetry, enriching logs with context, routing sensitive data to compliant storage, or customizing out-of-the-box templates.

This role is both a customer-facing product opportunity and an internal platform play for other Splunk and Cisco product teams. Success will require sharp roadmap strategy, clear prioritization, strong stakeholder management, and a passion for solving technical user problems from 0-to-1 and 1-to-n.

As Senior PM, You Will

• Own the vision and roadmap for pipeline-building capabilities that help customers create, iterate, and scale data processing workflows.
• Design intuitive experiences for admins, engineers, and technical users across visual pipeline building, reusable templates, stream-time transformations, and intelligent recommendations.
• Bring voice of the customer into product decisions, balancing technical depth with clarity, usability, and business impact.
• Drive market differentiation by staying ahead of trends in edge compute, data federation, stream processing, AI-assisted workflows, and enterprise data architecture.
• Collaborate across Splunk and Cisco, aligning engineering, design, customer success, field, GTM, and leadership stakeholders on roadmap priorities and tradeoffs.
• Help shape Splunk's long-term data federation strategy, influencing how enterprise data is managed across clouds, regions, and environments.

Minimum Qualifications

• Bachelor's with 8+ years; or Master's degree with 6+ years; or PhD with 3+ years of product management experience. Degree expected to be in Computer Science, Engineering, Data Science, Information Systems, or a related technical field.
• 5+ years of delivering technical products in one or more of the following domains: data platforms, cloud infrastructure, SaaS platforms, observability, security analytics, stream processing, data integration, or enterprise data management.
• Experience owning product strategy, roadmap, requirements, launch planning, and post-launch iteration for complex technical products used by administrators, developers, platform engineers, security teams, or other technical users.
• Experience partnering with engineering and design teams to deliver product capabilities involving APIs, user interfaces, data movement, data transformation, or large-scale distributed systems.
• Experience defining product success metrics, using customer feedback and usage data to prioritize roadmap decisions, and measuring adoption, business impact, or customer value after launch.

Preferred Qualifications

• Experience with data pipeline, stream processing, ETL/ELT, data lake, observability, security, or telemetry products, including technologies such as Kafka, Amazon Kinesis, Apache Spark, Flink, S3, Azure Data Lake, Databricks, Snowflake, or similar platforms.
• Familiarity with…