Webex Data Analytics Platform (WAP) engineering organization is responsible for developing the big data platform and core services at Webex. The platform and microservice ecosystem form the base on which other teams build analytics, data pipelines, and product capabilities.

We are looking for a Manager, Software Engineering, who will lead technical strategy and delivery for our platform and engineering teams. You will own program and project delivery, drive microservice and data-platform evolution, strengthen engineering processes, and champion AI adoption—working closely with engineering, product, and leadership to deliver high-impact outcomes on time and within scope. You will bring structure to ambiguity, visibility to complexity, and ensure our distributed teams operate efficiently and successfully.

• Lead end-to-end program and project delivery for sophisticated, cross-functional initiatives spanning microservice architecture, data platform, and engineering excellence.
• Define technical roadmaps, scope, objectives, success criteria, and key turning points in collaboration with engineering and product leadership.
• Own and evolve microservice architecture standards, API develop, service boundaries, and operational practices across the organization.
• Drive data platform strategy and execution: pipelines, storage, analytics, and ML infrastructure in partnership with data and platform teams.
• Establish and improve engineering processes (develop reviews, code quality, testing, CI/CD, incident response) and supervise KPIs for program health and delivery.
• Champion AI adoption and build high-performing engineering teams; identify use cases, prioritize initiatives, and foster a culture of continuous improvement.

• At least 12+ years of experience in software engineering, with 4+ years in engineering leadership, managing Software Engineering or Data Engineering teams.
• Strong track record of delivering large-scale, multi-team programs in microservice and/or data-heavy environments; deep experience with microservice architecture, cloud-native development, data platform and distributed systems.
• Strong oversight experience with data platforms: data pipelines, warehouses/lakes, streaming, and analytics/ML infrastructure.
• Experience defining and rolling out engineering processes (Agile/Scrum, compose reviews, CI/CD, SRE practices) and driving AI/ML adoption; proficiency with OKRs, KPIs, and roadmaps.
• Proficiency with program management tools such as Jira, Confluence, Asana, Smartsheet, or Microsoft Project.

• Ability to translate business and product requirements into technical specifications and actionable engineering roadmaps.
• Experience in regulated or high-availability domains (e.g. teamwork, fintech, healthcare, enterprise SaaS).
• Familiarity with modern data stack (e.g., Spark, Kafka, dbt, Snowflake/Databricks), ML platforms, and DORA-style metrics.
• Familiarity using AI tools (e.g., Copilot, Cursor, Codex) for efficiency and team adoption.

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