Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software bringing the power of cloud innovation to customers worldwide.
Living our values everyday results in our team-first culture and enables us to innovate grow and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment empowering our employees to be their authentic selves.
Manager Engineering Intelligence & Analytics
Role Summary:
We are looking for a senior leader to own and scale Five9s Engineering Intelligence function a capability that transforms raw engineering and business data into strategic insights that drive executive decision-making across a $100M engineering investment portfolio spanning 1800 features. This is not a traditional BI or reporting role. You will be the voice of engineering data translating complex delivery metrics into business narratives that shape portfolio prioritization resource allocation and organizational strategy.
You will inherit a strong foundation: a suite of operational dashboards and analytics tools already built and gaining traction with leadership. Your mandate is to productize these build real-time data infrastructure and evolve from reactive reporting to proactive intelligence that anticipates risks surfaces opportunities and quantifies business impact.
Responsibilities
Strategic Analytics & Executive Storytelling (40%)
- Own the end-to-end narrative of engineering investment: where money is being spent what value it is generating and where adjustments should be made
- Present quarterly and monthly insights to E-Staff and VP-level engineering leadership not just data but the story the so what and the recommended actions
- Build and maintain Feature Portfolio Intelligence: delivery predictions FTE allocation analysis resource contention identification and business value mapping
- Lead Quarterly Business Reviews for cross-functional product portfolio pods providing data-driven performance assessments
- Partner with Delivery Managers TPMs and Engineering Directors to ensure analytics directly address their decision-making needs
Platform & Data Engineering (30%)
- Architect the transition from existing dashboards to enterprise BI platform - Looker with real-time data feeds
- Design and build data pipelines integrating Jira (Structure Advanced Roadmaps) Jellyfish Salesforce Launch Darkly and internal systems via APIs
- Establish data quality frameworks automated validation and governance standards
- Eliminate manual data export/import workflows and achieve near-real-time data freshness
- Own the technical roadmap for the analytics platform
Stakeholder & Vendor Management (20%)
- Serve as the primary interface with analytics tool vendors (Jellyfish Looker/Google Atlassian) managing relationships feature requests and escalations
- Partner with IT and Data Engineering teams to align on data infrastructure access and security requirements
- Build trusted advisor relationships with Engineering VPs Product leadership and Finance to ensure analytics serves cross-functional needs
Team Building & Operational Excellence (10%)
- Hire mentor and develop the Engineering Analytics Engineer (immediate) and scale the team to 3-5 as the function matures
- Establish team processes: sprint cadence for analytics work intake/prioritization of requests SLAs for dashboard updates
- Build a self-service analytics culture where engineering teams can access insights without filing requests
- Document methodologies calculations and data lineage to ensure institutional knowledge
Skills competencies and qualifications
Required
- 8-12 years of experience in engineering analytics business intelligence data engineering or engineering operations/effectiveness ideally in a enterprise software environment
- Proven track record of building and scaling analytics functions or BI platforms from early stage to enterprise adoption
- Deep expertise with Looker / BI tools including data modeling dashboard design and performance optimization
- Strong technical skills: SQL (advanced) Python for data engineering REST API integration and ETL/ELT pipeline design
- Experience with engineering metrics frameworks (DORA SPACE or custom) and the ability to design measurement systems that balance quantitative rigor with organizational context
- Demonstrated ability to present data-driven insights to VP/C-level audiences and translate complex metrics into actionable business narratives
- Experience managing vendor relationships and tool ecosystems at scale
- Strong understanding of software delivery lifecycle Agile methodologies and how engineering organizations operate
Preferred
- Experience with Jira (including Structure Advanced Roadmaps) and Jellyfish or similar engineering management platforms
- Familiarity with Salesforce data and the ability to connect customer/case data and revenue related data to engineering delivery metrics
- Experience building data pipelines on cloud platforms (GCP) with tools like BigQuery
- Background in engineering operations developer experience or engineering effectiveness not just pure data science
Key stakeholders include:
- Engineering Service Owners
- Product Managers and Product Operations
- Engineering Operations Delivery Managers Technical Program Managers