Senior Manager, Data Visualization & Tooling - McD Tech Labs

    • Mountain View, CA

Job Description

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Company Description

We are proud to be one of the most recognized brands in the world, with restaurants in over 100 countries and billions of customers served each year. McDonald's is people business just as much as we are a restaurant business. We strive to be the most inclusive brand on the globe by building a workforce with different strengths who make delicious, feel good moments that are easy for everyone to enjoy.

At McDonald's, we are dedicated to using our scale for good: good for people, our industry and the planet. We see every single day as a chance to have a lasting impact on our customers, our people and our partners. We will continue to pursue big, global initiatives while remaining kind neighbors and supporters of our local communities.

We are moving fast and are building a passionate team to help us. This means the company is looking for innovators, leaders, sprinters who are focused on crafting memorable experiences for our customers, employees and partners. Joining McDonald's means thinking big daily and preparing for a career that can have impact around the world.

Job Description

McD Tech Labs is the recently established Silicon Valley based technology development group within McDonald's Corporation. Our mission is to deliver advanced technology solutions that address real-world, data-driven needs in the McDonald's Restaurant environment. We are focused on using state-of-the-art Machine Learning, AI, and related technologies along with McDonald's unparalleled scale to completely transform the customer experience!

We are currently looking for a talented data engineering leader to establish and lead our data visualization and tooling team at McD Tech Labs. This role reports directly to the Head of Data for McD Tech Labs. The leader will be tasked with defining and building data visualization and tooling framework, working within data org and cross functionally with both internal and external customers, partners and leadership. The visualization aims to enable efficient analysis and understanding of performance of ML products and data operating at petabyte scale aggregated from large, diverse sets of stores, regions and countries worldwide.

The ideal candidate will have previous experience leading a team of data application engineers working on large-scale data visualization and tooling products and a passion for building agile, high-performing teams.

Responsibilities:

  • Define vision and drive execution of data visualization and tooling roadmap in support of overall product/engineering roadmap
  • Work cross-functionally with ML researchers, engineers, data scientists and analysts to innovate on and optimize state-of-the-art visualization of large-scale ML data, metrics and analytics
  • Build data visualization and tooling-as-a-service for internal and external data consumers
  • Develop custom web visualizations with modern technologies such as React, JavaScript and TypeScript and libraries such as D3, Plotly, Matplotlib
  • Integrate with diverse sources of data and visualization with BI tools such as Tableau/Looker and Notebook tools such as Jupyter and Zeppelin
  • Train and support a diverse and large set of data users from internal to external


Qualifications

  • Bachelors in Computer Science or equivalent experience
  • Minimum of 5 years of experience in data visualization and tooling with demonstrated experience leading a team of data application engineers
  • Excellent web development experience leveraging modern frameworks and standards such as React, Typescript/Javascript, CSS, D3 and Plotly
  • Strong experience in building state-of-the-art data visualization and tooling for large scale, preferably ML, data products
  • Proven understanding SQL, query and data systems
  • Proven ability to execute resourceful Agile development with sometimes ambiguous, conflicting requirements to be delivered in a pragmatic timeline.


Additional Information

All your information will be kept confidential according to EEO guidelines.


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