Sr Mgr, Business Intelligence Product Owner

Equinix•Dallas, TX

1d•Onsite

About The Position

Our Enterprise Data & Analytics (EDNA) organization is transforming today’s fragmented, ad-hoc reporting landscape to a unified, self-service platform that empowers analytics communities across Equinix's $10B+ global business. We are building a modern BI infrastructure composed of enterprise semantic layers, dimensional data models, analytics-ready "Explores," and self-service governance frameworks. This transformation will enable faster decisions, eliminates metric inconsistencies, and unlocks advanced analytics capabilities. We are looking for a Senior Manager, Business Intelligence Product Owner to drive the day-to-day execution of our self-service BI platform roadmap. You will translate strategic product vision into executable work for Visual Engineers and Data Engineers, manage sprint-level prioritization, write detailed technical specifications, and ensure on-time delivery of high-quality data products. This role is the critical bridge between business requirements and engineering execution, working hands-on with cross-functional teams to deliver semantic layer capabilities, Subject Area Explores, and governed metrics that enable enterprise-wide self-service analytics.

Requirements

5-7+ years in Analytics Engineering, Business Intelligence, Data Engineering, or Technical Product Ownership roles
Hands-on experience with modern data stack tools: dbt, LookML (Looker), SQL, cloud data warehouses (BigQuery, Snowflake, or Databricks)
Deep understanding of dimensional modeling (star schema, fact/dimension tables) and semantic layer concepts (metrics, measures, dimensions, business logic layers)
Proven track record managing agile backlogs, writing user stories, and driving sprint execution for engineering teams using Jira or similar tools
Strong facilitation skills for sprint ceremonies: standups, grooming, planning, demos, retrospectives
Ability to decompose complex business requirements into sprint-sized, technically executable increments with focus on delivery velocity, quality, and stakeholder satisfaction
Excellent written and verbal communication skills; ability to translate between business language and technical specifications
Experience partnering with cross-functional teams including Analytics Engineers, Data Engineers, Business Analysts, and business stakeholders
Comfortable working in fast-paced, ambiguous environments with evolving requirements and competing priorities; skilled at managing expectations, negotiating priorities, and communicating trade-offs
Bias for action: moves quickly to unblock teams, clarify ambiguity, and drive decisions
Detail-oriented: ensures specifications are complete, accurate, and unambiguous before assigning to engineers
Proactive: identifies risks and dependencies early; escalates issues before they become critical blockers; uses data (velocity metrics, defect rates, cycle time) to identify process improvements

Responsibilities

Own and maintain the BI platform engineering backlog in Jira, writing detailed user stories with clear acceptance criteria for Analytics Engineers (LookML, Explores, metrics) and Data Engineers (gold layer models, pipelines, transformations)
Conduct daily standups, sprint planning, grooming sessions, and retrospectives with engineering teams to unblock issues, clarify requirements, and ensure sprint commitments are on track
Track velocity, burn-down, and delivery metrics; escalate risks and dependencies that threaten delivery timelines to project team
Partner with Domain Portfolio Managers to decompose high-level business requirements into sprint-sized, technically precise user stories
Document detailed specifications including source system mappings, data transformation logic, business rules, metric calculations, aggregation strategies, performance requirements, and data quality expectations
Validate specifications are complete and unambiguous before assigning to engineering, working with Business Systems Analysts to ensure data mappings are accurate and feasible
Identify and manage dependencies across Analytics Engineering, Data Engineering, Platform, and Governance teams; coordinate delivery when multiple teams contribute to a single data product
Conduct user acceptance testing (UAT) for new Subject Area Explores, curated dashboards, and semantic layer metrics before production deployment; own production readiness checklist (performance, security, documentation, training materials)
Provide regular status updates to stakeholders on sprint progress, delivery timelines, and scope changes; run demos showcasing newly delivered capabilities