Director of Service and Customer Operations - Construction Automation

About this role

As a Senior Business Intelligence Engineer within the Customer Service Analytics team at Audible, you'll serve as a data-driven decision enabler for our Customer Service leadership team. You'll be responsible for designing, implementing, and optimizing the reporting processes that deliver critical KPIs and business insights across our organization.

Working with loosely defined problems, you'll transform complex data into clear, actionable narratives. Your role will be pivotal in maintaining data governance standards while making insights readily accessible through efficient, self-service data solutions.

You're a data storyteller who balances technical expertise with strong business acumen, particularly in the world of content. You excel at working cross-functionally, translating business requirements into robust analytical frameworks. You're naturally curious, with an ability to look beyond immediate data requests to identify the underlying strategic questions that drive our Customer Service. You thrive in ambiguous situations, delivering independently with minimal guidance while continuously improving data processes.

Your communication skills are exceptional, allowing you to distill complex analyses into compelling insights for both technical and executive audiences. You establish strong relationships with your stakeholders that earn trust and influence decision-making.

• Design, implement, and optimize BI solutions that effectively track KPIs and provide insights for business reviews and executive reporting, and develop dashboards that enable self-serve access to data, ensuring speed, reliability, and scalability.
• Break down high-level business metrics into constituent components and leading indicators that provide actionable insights for leadership as part of monthly and quarterly business reviews.
• Be a proactive thought partner, anticipating leadership questions and developing analyses and visualizations that address emerging business needs.
• Automate the identification of key contributing dimensions to metric variance, enabling faster root cause analysis.
• Develop concise, impactful data visualizations that communicate complex trends and insights effectively to executive audiences.
• Develop clear documentation that bridges technical implementation with business context, enabling both technical and non-technical stakeholders to understand reporting methodologies.
• Communicate findings and insights to stakeholders in a clear, concise, and actionable manner.
• Balance stakeholder requirements with technical constraints while maintaining a focus on long-term solutions.
• Serve as a data governance advocate, ensuring consistency in metrics definitions and data quality.
• Partner with data scientists, engineers, product managers, and business leaders to align reporting with strategic objectives.
• Invest in stakeholder relationships that build trust and enable insights to influence business decision-making.