Jonathan Palmer is the former VP of Data at Scopely, a US-based unicorn behind hit mobile games such as Monopoly GO!.

He grew and led the data team at Scopely to 50 people, mostly based in Barcelona.

Before that, Jon was Product Director for Core Data Services at King, the Swedish unicorn behind the hit game Candy Crush. He was also Head of BI at GoCardless, the British unicorn. And he is now field CTO at Omni, the BI & AI Analytics platform.

We cover:

🔥 Workstream #1: scaling the data organization from 10 to 50 people (main teams, organization…)

🔥 Workstream #2: building a modern data stack to improve performance, simplify hiring, and support hypergrowth

🔥 Workstream #3: evolving roles, developing leaders, and adapting the organization as the company scaled

🔥 The biggest challenges: imposter syndrome, managing change, and cultural differences

📚 RESOURCES

- Jon’s Linkedin profile

- The book What I Talk About When I Talk About Running by Haruki Murakami

🎬 CHAPTERS

00:00 What's Scopely?

01:52 The context when he arrived

02:41 Organizing the data team

08:45 Building a Modern Data Stack

13:44 Adapting the team to new needs

15:37 Fighting the imposter syndrome

16:57 Leading a big team

20:23 Managing cultural differences

23:15 Why he joined Omni

25:00 Jon’s favorite resources

26:13 His best advice

🤩 OTHER EPISODES YOU SHOULD LOVE

#8 - Marshmallow: Building the data analytics team at a unicorn

#4 - Ex-VP of Product at Looker, he launched Omni, the challenger in Business Intelligence

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

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Colin Zima is the co-founder and CEO of Omni, the Business Intelligence platform recently valued at over $1.5 billion. Before founding Omni, Colin was VP of Product and Chief Analytics Officer at Looker, the Business Intelligence platform acquired by Google for $2.6 billion.

He shares his predictions on the future of analytics:

🔥 Prediction #1: The dashboard is changing, not going away

🔥 Prediction #2: There will always be a place for data teams

🔥 Prediction #3: Natural language doesn't mean simple question and answer

🔥 Prediction #4: AI will start writing more data models than people

🔥 Prediction #5: Semantics matter more than ever

❤️ SPONSOR

This episode is made possible by Omni, the next-generation BI platform already used by many companies (Brevo, Photoroom, etc.).

👉 Colin’s Linkedin Profile

📚 RESOURCES

- Colin’s Linkedin Profile

🎬 CHAPTERS

00:00 “The dashboard is changing, not going away”

13:00 "There will always be a place for data teams"

16:11 “Natural language doesn't mean simple question and answer”

25:31 “AI will start writing more data models than people”

27:38 “Semantics matter more than ever”

28:17 SQL vs Semantic Layer

35:37 The data team of the future

🤩 OTHER EPISODES YOU SHOULD LOVE

#4 - Ex-VP of Product at Looker, he launched Omni, the challenger in Business Intelligence

#8 - Marshmallow: Building the data analytics team at a unicorn

#96 - Deezer : How I restructured the Business Analytics team and made it more Business-Focused

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2/ Leave a 5 stars review on Apple Podcasts here 🥰

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Tanmay Nagori is Head of Data & Analytics for Lending at Tide, the UK-based fintech unicorn. Tide helps SME businesses save time by providing banking, payment, administrative, and financial tools. Today, it is used by 1.8 million SMEs in the United Kingdom, India, Germany, and France.

We cover :

🔥 His journey from Analyst to Head of Analytics (Consulting, Amazon…)

🔥 How the data team is organized globally and what stack they use

🔥 The approach and tools they implemented to increase the business impact of analytics

🔥 His view on how AI changes the role of the analytics team (from insights to actions)

📚 RESOURCES

- Tanmay’s LinkedIn Profile

- The book "A Technique for Producing Ideas" by James Webb Young

- The book "Thinking, Fast and Slow" by Daniel Kahneman

🎬 CHAPTERS

00:00 What's Tide?

01:53 Tanmay’s journey

05:39 Their main analytics projects

08:19 Their stack

10:50 His main challenges

13:53 His career advice

15:55 Resources he recommends

🤩 OTHER EPISODES YOU SHOULD LOVE

#8 - Marshmallow: Building the Data Analytics Team for a unicorn

#6 - HelloFresh: Building and scaling a Product Analytics culture

#2 - Deezer: How I restructured the Business Analytics team and made it more Business-Focused

👋 MORE DATA CONTENT?

1/ Follow me on LinkedIn here 🤳

2/ Sign up for the newsletter (summaries, events) here 💌

3/ Check out the podcast in video format on YouTube here 📹

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Ina Vaduvescu is director of analytics at Marshmallow, the UK-based unicorn that offers affordable car insurance for newcomers to the UK. The scaleup raised $90 million in 2025 at a $2 billion valuation. She leads a team of 12 analysts and has spent the past few years building and structuring the analytics function.

We cover :

🔥 Her journey, from data analyst to director across startups and scale-ups

🔥 How she structured a high-performing and standardized data team

🔥 The KPI tree framework that was transformative to how they operate

🔥 Their AI projects: AI analytics and customer support AI agent

📚 RESOURCES

- Ina’s LinkedIn profile

- The newsletter TLDR

- Lenny's Podcast

🎬 CHAPTERS

00:00 What's Marshmallow ?

00:39 Ina's journey

02:48 #1 - recruitment & stack

10:23 #2 - better prioritization

15:34 #3 - self-service & AI analytics

21:55 #4 - AI project for customer support

27:06 Their main challenges

28:05 Their next steps

30:04 The resources she recommends

30:41 Her career advice

🤩 OTHER EPISODES YOU SHOULD LOVE

#7 - Flix: Leveraging data to scale operations 

#5 - N26: Building and scaling the Data team for Marketing

#2 - Deezer: How I restructured the Business Analytics team and made it more Business-Focused

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Manoj Raghavan is a Staff Data Strategist at Flix, the affordable travel tech scaleup based in Germany, solving technology for long-distance buses and trains. Flix operates in 40+ countries, has 5,000 employees, including around 100 data & AI experts.

We cover :

🔥 Their data organisation: decentralized and with no central data leadership

🔥 One of the main projects he worked on to improve customer experience: bus partner classification

🔥 Their stack: AWS, Snowflake, dbt, Power BI…

🔥 One of their main current challenges: build vs. buy when it comes to AI tools

📚 RESOURCES

- Manoj’s LinkedIn profile

- The book of book Chip Huyen Designing Machine Learning Systems

- The book of book Chip Huyen AI Engineering

🎬 CHAPTERS

00:00 What is Flix?

02:38 Manoj's journey

06:28 The Data team organization

10:43 One of his main projects

16:35 Their stack

19:02 Their main challenges

21:17 Their next step

23:40 Resources he recommends

24:42 His career advice

🤩 OTHER EPISODES YOU SHOULD LOVE

#6 - HelloFresh: Building and scaling a Product Analytics culture

#5 - N26: Building and scaling the Data team for Marketing

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

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Florian Bonnet is a former Director of Product at HelloFresh. He later held product leadership roles in scale-ups such as Typeform and Fintechture. He is currently VP of Product Management at Veriff, the Estonian unicorn.

We cover :

🔥 #1 - How to define the metrics (North Star, KPI Tree…)

🔥 #2 - How to manage product performance with data on a weekly basis

🔥 #3 - How to implement the right collaboration between Product & Data

🔥 His 2 main challenges and his views on GenAI for Product Analytics

📚 RESOURCES

- Florian’s LinkedIn profile

- His book The Power of Analytics

- Matt Watkinson's book The Grid

🎬 CHAPTERS

00:00 What is HelloFresh?

01:32 Florian’s journey from Data Analyst to Director of Product

03:16 The context at HelloFresh when he became Director of Product

05:49 #1 - How to define the metrics (North Star, KPI Tree…)

08:30 #2 - How to manage product performance with data on a weekly basis

12:17 #3 - How to implement the right collaboration between Product & Data

15:38 His main challenges

18:53 The tech stack he recommends

21:04 The impact of GenAI on Product Analytics

25:48 Florian’s favorite resources

28:14 His best advice

🤩 OTHER EPISODES YOU SHOULD LOVE

#5 - N26: Building and scaling the Data team for Marketing

#4 - Ex-VP of Product at Looker, he launched Omni, the challenger in Business Intelligence

#2 - Deezer : How I restructured the Business Analytics team and made it more Business-Focused

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

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Mathias is Head of Data for Marketing at N26, the Berlin-based neobank valued at over $9 billion. He joined as a Senior Data Analyst in May 2020 and has since scaled the team to 12 people.

We address :

🔥 His journey to becoming Head of Data for Marketing at N26

🔥 His main projects: Marketing Mix Modeling, User Value Modeling, Data Governance & Data Quality

🔥 The data stack at N26: AWS, Snowplow, dbt, Redshift, Metabase…

🔥 His main challenges: scale-up volatility and the classic imposter syndrome

📚 RESOURCES

- Mathias’s LinkedIn profile

- The book of Zhamak Dehghani Data Mesh : Delivering Data-Driven Value at Scale

- The book of Joe Reis & Matt Housley Fundamentals of Data Engineering: Plan and Build Robust Data

- The book of Gene Kim, Kevin Behr and George Spafford The Phoenix Project

- The book of Gene Kim The DevOps Handbook

- The book of Gene Kim The Unicorn Project

- The book of Gene Kim, Jez Humble and Nicole Forsgren PhD Accelerate

🎬 CHAPTERS

00:00 Introduction to N26

03:25 How he became Head of Data for Marketing at N26

10:49 1st project: implementing a Marketing Mix Model

17:36 2nd project: building a User Value Model

20:57 3rd project: Data Governance & Quality

23:37 The data stack at N26

25:16 The biggest challenges

29:29 What’s next: decision automation

31:11 Mathias’s favorite resources

32:14 Why he loves working in data

🤩 OTHER EPISODES YOU SHOULD LOVE

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

#2 - Deezer : How I restructured the Business Analytics team and made it more Business-Focused

#3 - Aircall: Adapting the Data Strategy to the slowing economic environment

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

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Colin is the co-founder & CEO of Omni, the Business Intelligence tool that has seen rapid adoption over the past years. By 2025, Omni had raised $69 million and reached a valuation of $650 million. Many data leaders are now choosing to abandon their traditional BI tools in favor of Omni.

We address :

🔥 Why Colin left his role as VP of Product at Looker to build a new BI tool

🔥 The Omni vision: reconciling enterprise BI governance with the flexibity of Excel and SQL

🔥 AI for Analysis (”chat with your data”): what Omni did differently in its Semantic Layer to make it work

🔥 The future of Data teams when anyone can do complex analyses in minutes

❤️ SPONSOR

This episode is made possible by Omni, the next-generation BI platform already used by many companies (Brevo, Photoroom, etc.).

👉 Discover the demos

📚 RESOURCES

- Colin's LinkedIn

- Jason Lemkin’s SaaStr blog

- Dave Kellog’s Kellblog blog

- Demos on the Omni website (Build in Public)

🎬 CHAPTERS

00:00 Colin’s career path

01:37 Omni’s initial vision

05:07 From Looker to Omni

09:42 Why data leaders choose Omni

15:53 AI for Analysis (”Chat with your data”): what Omni did differently in its Semantic Layer to make it work

20:12 “Building in public” at Omni

24:36 The evolution of data teams

30:58 The specifics of the French market

32:30 Colin’s resource recommendations

33:13 What he likes most about data

🧐 OTHER EPISODES

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

#2 - Deezer : How I restructured the Business Analytics team and made it more Business-Focused

#3 - Aircall: Adapting the Data Strategy to the slowing economic environment

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

Hosted on Acast. See acast.com/privacy for more information.

Edouard Flouriot is Director of Data at Aircall, the phone and communication platform designed for sales and support teams. Active in more than 100 countries with more than 10,000 customers, Aircall achieved centaur status after securing over $100 million in annual recurring revenue in 2022. In this episode, Edouard is sharing insights on its biggest recent challenge, which is: how to adapt the data strategy to the slowing economic environment?

We address:

🔥 The overall economic context for scaleups: going from hyperscale to a slower controlled growth

🔥 His conviction that this context requires more centralisation rather than decentralisation (aka Data Mesh)

🔥 How centralisation enables more governance and control over costs and ressource management

🔥 The initiatives that they launched around 3 pillars: cost tracking, project structure and culture shift.

🎬 CHAPTERS

00:00 Trailer

00:43 Introduction

01:41 The context

04:33 The 3 key implemented actions

05:02 1st action: shifting the culture towards more control and governance

07:38 2nd action: being more budget conscious by optimizing current tools & migrating to new ones

10:47 Focus on Fivetran & Looker

13:30 3rd action: identifying where to invest the efforts to better structure projects

18:01 The other challenges Edouard faced

20:00 Edouard’s ressource recommendations

21:07 What he likes most about data

21:51 What made him improve the most

22:47 The best advice Edouard ever received

📚 RESSOURCES

- The book Trillion Dollar Coach

- The article “The Next Era of Data at Instacart” by Nate Kupp

🧐 OTHER EPISODES

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

#2 - Deezer : How I restructured the Business Analytics team and made it more Business-Focused

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

Hosted on Acast. See acast.com/privacy for more information.

Thibaud Arbes Dupuy is Director of Operational Performance at Deezer, the French music streaming unicorn with 9 figures in revenue and +600 employees. Two years ago, in an urge to become more profitable, the CEO asked him to took over the Data Analytics team to make it business-focused. A challenge he took up successfully through a multi-dimensional strategy.

We address :

🔥 His career path to become Director of Operational Performance at Deezer,

🔥 The 4 pillars of his strategy: bring business focus, reorganize the team, retain talents and recruit the best,

🔥 His biggest difficulty: being patient and asking the other teams to be patient too,

🔥 His main advice when it comes to managing a team without any prior data experience.

🎬 CHAPTERS

00:00 Trailer

01:14 Introduction

02:11 His career from Finance to Director of Operational Performance at Deezer

07:14 Thibaud’s 1st strategy pillar: bring business focus in his team

10:49 Thibaud’s 2nd strategy pillar: organize the Business Analytics team

15:12 Thibaud’s 3rd strategy pillar: retain talents

20:27 Thibault's 4th strategy pillar: recruit the best

25:47 His biggest challenges: being patient and asking other teams to be patient too

27:16 His advice to manage a Data team with no data experience

28:09 The next steps of the Business Analytics team

29:24 Thibaud’s ressource recommandations

29:50 What he like most about data

30:36 What made him progress the most

31:53 The best advice Thibaud ever received

📚 RESSOURCE

DoorDash tech blog

🧐 OTHER EPISODES

#1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data

#3 - Aircall: Adapting the Data Strategy to the slowing economic environment

🎙 SUPPORT THE PODCAST FOR FREE

1/ Subscribe 🔔

2/ Leave a 5 stars review on Apple Podcasts here 🥰

Hosted on Acast. See acast.com/privacy for more information.