Who am I

As a data practitioner for almost 20 years, I am passionate about all aspects of how organizations can apply data to improve the decisions they make. My career began focused on financial analytics, but for the last ten years I have been building and leading data teams across a variety of industries. The areas I focus most on at present are:

• Applied data in decision making: How can companies better integrate analytics and data science into their processes and activities to be more effective?
• Organizational development: How can I most effectively cultivate a highly enabled, high performance data team? How can I empower the organization through tooling and training to allow everyone to act as an analyst?
• Engineering and architecture: Given the roadmap we’re on and the rapidly evolving data technologies, what changes should I be making today to be on the forefront tomorrow to tackle our organization’s problems?

Throughout my tenure, I have maintained an active hands-on role in contributing the team’s technology. This includes development in SQL, Python, Tableau, and a number of other tools

Past Roles:

These are my most recent roles leading data teams. For a full overview of my experience, please consult my LinkedIn

Head of Data Products at Miro

In my most recent role, I lead Data Product efforts at Miro, an online collaboration platform. In a nutshell, we made sure data is delivered, is accurate and complete, and is usable by the analytics team.

My team consisted of a mixture of Data Engineers, Analytics Engineers, and Technical Product Managers to deliver the data products and infrastructure Miro needs to run its analytics. In detail, the team is focused on:

• Data Pipelines: Delivering the data ingestion and integration needed for Miro to have access to all its data assets. Beyond just delivering data, we have designed a framework to orchestrate, observe, and guarantee data to our consumers
• Quality and Observability: We were responsible for ensuring all data is correct and for detecting changes and variations in both incoming data and products presented to the business
• Transformation and Models: Our team built and managed the bulk of data models/products created via dbt in snowflake and own overall architectural design and strategy, including our company data warehouse
• Training and Tooling: Our team educated all analysts on how to use data models effectively and builds and maintains the tools and platforms they use to do their jobs

Senior Director, Data at Navan

At Navan, my goal was to build a data team, platform, and strategy effectively from the ground up. Beginning from a small team, I ultimately created a globe-spanning 30-person team to empower users on five continents to use data to drive decisions. Some of the capabilities we built include:

• Best-in-class data platform: A near-real-time, highly consistent and available data platform that operated in multiple regions and ensured consistency, accuracy, and completeness of the data. Built using a mixture of open source and commercial technologies, our platform enabled dozens of use cases and data products
• Self-service BI and insights: Our BI platform and holistic approach to education and enablement enabled hundreds of end users to generate their own insights, create their own reporting, and work with data without any dependency on the data team to pull data
• Machine learning/ AI in the product: Using in-house developed algorithms and technology, we put more than two dozen ML models into production to both improve the product experience and to support decision making by our operational teams