Inside the Data Stacks of Industry Titans: Insights from WeWork, Financial Times, and More

Building a modern data stack is like designing a blueprint for a city (a futuristic, well-planned city, of course!) Every building, road, and system is meticulously designed to serve its purpose. It is no longer enough to gather data. You need the infrastructure that transforms raw information into actionable insights, much like a city’s infrastructure converts resources into sustainable growth.

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Leading organizations like Financial Times, Samsara, and Pleo have not only built robust data ecosystems but have also turned them into engines of growth and innovation. They aren’t just solving today’s challenges, they are future-proofing their operations. Their data stacks are designed to scale, collaborate, and adapt to meet the evolving needs of their businesses.

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In this blog, we will explore how these industry leaders are crafting their data stacks, the tools they rely on, and how their innovative approaches are setting benchmarks for the future. Whether you're a seasoned data leader or an emerging enthusiast, these lessons will inspire you to think bigger and design better.

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1. Building a strong foundation: the role of data warehouses

A solid foundation is critical for any structure, and in the world of data, that foundation is the data warehouse. It’s the cornerstone where raw data is stored, transformed, and prepared for use. Leaders across industries recognize the importance of choosing the right data warehouse and have strategically integrated tools to support their needs.

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Financial Times needs to handle a large amount of data, this is how they solve for it.

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‍“We rely on BigQuery as our central data warehouse, and it serves as the backbone of our self-service BI tools like Looker and Amplitude. BigQuery’s ability to handle vast amounts of data with speed and scalability makes it indispensable for us. Its integration with other tools in our stack, like Looker, ensures that our teams can seamlessly access and analyze data in real-time. This has been critical for maintaining our competitive edge in the media industry, where timely insights are everything.”
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–McKinley Hyden, Director of Data Value and Strategy, Financial Times
How Financial Times Built Data Capabilities Worth £3.2M (and counting!)‍‍

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Samsara follows a hybrid approach and their data stack varies based on the purpose and speed.

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‍“Our approach to warehousing is hybrid. We use Databricks for scale and BigQuery for high-speed analytics.
Databricks allows us to process and analyze streaming data at scale, making it ideal for operational use cases, while BigQuery’s speed and flexibility cater to ad hoc and real-time analytics. This dual setup ensures that we can meet the diverse needs of our teams without compromising on performance.”

– Kiriti Manne, Head of Strategy & Data, Samsara
How Samsara’s Attribution Model Turns Data into Gold

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WeWork prioritizes ease of use and a cloud-native architecture. That is why they chose Snowflake.

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‍“Snowflake serves as our data warehouse, allowing us to centralize data while keeping it accessible for downstream applications like Tableau and Airflow. We chose Snowflake because of its cloud-native architecture and ease of use. It allows our teams to collaborate on data without worrying about performance bottlenecks. The seamless integration with Tableau means our teams can visualize data instantly, which is invaluable during decision-making processes.”

– Thomas Dodson, Head of Engineering and Data, Ex-WeWork
How data helped WeWork exit bankruptcy

2. Orchestrating data workflows: managing complexity with ease

Data orchestration is akin to a symphony conductor, ensuring every instrument (or tool) plays its part harmoniously. Effective orchestration tools enable organizations to manage, automate, and optimize their data workflows seamlessly.

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Pleo uses multiple data tools and still manages to maintain consistency and reliability across the board. This is how they achieve it.

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‍“We use Airflow for orchestration and dbt for transformation, ensuring our data workflows are not only reliable but scalable. Airflow is critical for automating complex workflows, especially when dealing with large-scale data ingestion from tools like Fivetran and Segment. dbt complements this by providing a framework for transforming and organizing our data, ensuring consistency and reliability across the board.”

– Sriram Sampath, Head of Data Analytics, Pleo
Pleo's proactive data strategy for customer success

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Here is an overview of Malt’s data stack. 

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“Composer, Google Cloud’s managed Airflow service, is the backbone of our orchestration efforts. Managing data pipelines can get incredibly complex as you scale, and Composer simplifies that process by providing a managed solution. It allows us to focus on building and optimizing workflows rather than spending time on infrastructure management. Combined with Airbyte and Fivetran for ingestion, it ensures our data is always ready for analysis.”

– Anaïs Ghelfi, Head of Data Platform, Malt
Malt’s data ROI framework to prove your data team’s worth in big, bold numbers

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Here is how Moonpay ensures flexibility across global teams with their data stack. 

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“We lean on Airflow for orchestration, integrating it seamlessly with GCP and Looker. Airflow gives us the flexibility to schedule and monitor workflows across multiple time zones, ensuring data availability 24/7. This is especially important as we operate globally, and teams depend on timely data for decision-making.”

-Emily Loh, Director of Data, MoonPay
MoonPay’s blueprint for cracking self-serve analytics 

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3. Self-service analytics: democratizing access to insights

Empowering teams with self-service analytics is like handing out keys to a treasure chest of insights. By democratizing data access, organizations ensure every stakeholder has the tools to make data-driven decisions.

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‍“Our self-service analytics platform, powered by Looker, enables teams to access data without waiting for analysts. Looker has revolutionized how we deliver insights across the organization. Its intuitive interface and powerful capabilities make it easy for non-technical users to explore data independently, reducing bottlenecks and empowering teams to act faster on insights.”

– McKinley Hyden, Director of Data Value and Strategy, Financial Times
How Financial Times Built Data Capabilities Worth £3.2M (and counting!)

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‍“We’ve made Looker the face of our self-service platform. Looker’s robust semantic layer ensures that all teams have access to accurate and consistent data. By enabling self-service, we’ve not only improved efficiency but also fostered a culture of data-driven decision-making across the organization.”

– Emily Loh, Director of Data, MoonPay
MoonPay’s blueprint for cracking self-serve analytics 

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4. Quality and governance: ensuring trust in data

Data is only as good as its quality. Establishing robust governance frameworks and monitoring mechanisms ensures that data remains accurate, consistent, and reliable.

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Freshworks chooses a highly scalable and flexible approach to managing data and their enterprise needs. 

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“We rely on Databricks as our primary data platform and Snowflake for data warehousing, supported by AWS and GCP as our underlying cloud services. Our approach is highly scalable and flexible, with open-source tools integrated for specific use cases. For BI, Power BI remains our go-to, providing user-friendly dashboards that cater to a wide range of stakeholders. This combination allows us to address scaling challenges while delivering actionable insights tailored to our enterprise needs.”

Sachin Mishra, Senior Director of Data Science and AI, Freshworks
Leveraging AI to make data accessible across Freshworks

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‍‍“Data quality is paramount for us, and tools like Elementary allow us to monitor and improve our pipelines proactively. Elementary provides visibility into our data health, enabling us to catch anomalies early and ensure that our insights are always reliable. This proactive approach to quality has been instrumental in building trust in our data systems.”

– Sriram Sampath, Head of Data Analytics, Pleo
Pleo's proactive data strategy for customer success

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Designing your own data blueprint

The data stacks of companies like Financial Times, Samsara, and Pleo aren’t just collections of tools, they are thoroughly designed ecosystems that align with their business goals. From choosing the right data warehouse to empowering teams with self-service analytics, these organizations show that success lies in thoughtful planning, strategic investment, and a relentless focus on impact.

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Want to learn more about how top data leaders are navigating their challenges and driving innovation? Check out the People of Data podcast on Spotify and gain deeper insights from the leaders shaping the future of data.