Explore every episode of the podcast DataGen Europe
| Title | Pub. Date | Duration | |
|---|---|---|---|
| #9 - Tide: From Dashboards to Decision Boards with AI | 17 Jun 2026 | 00:17:20 | |
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 : š„ His journey from Analyst to Head of Analytics (Consulting, Amazonā¦) š„ How the data team is organized globally and what stack they use š„ The approach and tools they implemented to increase the business impact of analytics š„ His view on how AI changes the role of the analytics team (from insights to actions) š RESOURCES - Tanmayās LinkedIn Profile - The book "A Technique for Producing Ideas" by James Webb Young - The book "Thinking, Fast and Slow" by Daniel Kahneman š¬ CHAPTERS 00:00 What's Tide? 01:53 Tanmayās 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 š¤© 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 š MORE DATA CONTENT? 1/Ā Follow me on LinkedIn hereĀ š¤³ 2/Ā Sign up for the newsletter (summaries, events) hereĀ š 3/Ā Check out the podcast in video format on YouTube hereĀ š¹ š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #8 - Marshmallow: Building the data analytics team at a unicorn | 03 Jun 2026 | 00:32:21 | |
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 : š„ Her journey, from data analyst to director across startups and scale-ups š„ How she structured a high-performing and standardized data team š„ The KPI tree framework that was transformative to how they operate š„ Their AI projects: AI analytics and customer support AI agent š RESOURCES - Inaās LinkedIn profile - The newsletter TLDR š¬ 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 š¤© OTHER EPISODES YOU SHOULD LOVE #7 - Flix: Leveraging data to scale operationsĀ #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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #7 - Flix: Leveraging data to scale operations | 22 Apr 2026 | 00:26:57 | |
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 : š„ Their data organisation: decentralized and with no central data leadership š„ One of the main projects he worked on to improve customer experience: bus partner classification š„ Their stack: AWS, Snowflake, dbt, Power BIā¦ š„ One of their main current challenges: build vs. buy when it comes to AI tools š RESOURCES - Manojās LinkedIn profile - The book of book Chip Huyen Designing Machine Learning Systems - The book of book Chip Huyen AI Engineering š¬ 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 š¤© 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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #6 - HelloFresh: Building and scaling a Product Analytics culture | 16 Mar 2026 | 00:30:26 | |
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 : š„ #1 - How to define the metrics (North Star, KPI Treeā¦) š„ #2 - How to manage product performance with data on a weekly basis š„ #3 - How to implement the right collaboration between Product & Data š„ His 2 main challenges and his views on GenAI for Product Analytics š RESOURCES - Florianās LinkedIn profile - His book The Power of Analytics - Matt Watkinson's bookĀ The Grid š¬ CHAPTERS 00:00 What is HelloFresh? 01:32 Florianās 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 Treeā¦) 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 Florianās favorite resources 28:14 His best advice š¤© 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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #5 - N26: Building and scaling the Data team for Marketing | 04 Feb 2026 | 00:33:31 | |
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 : š„ His journey to becoming Head of Data for Marketing at N26 š„ His main projects: Marketing Mix Modeling, User Value Modeling, Data Governance & Data Quality š„ The data stack at N26: AWS, Snowplow, dbt, Redshift, Metabaseā¦ š„ His main challenges: scale-up volatility and the classic imposter syndrome š RESOURCES - Mathiasās 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,Ā Kevin Behr andĀ George SpaffordĀ 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 š¬ 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 Whatās next: decision automation 31:11 Mathiasās favorite resources 32:14 Why he loves working in data š¤© 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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #4 - Ex-VP of Product at Looker, he launched Omni, the challenger in Business Intelligence | 21 Jan 2026 | 00:34:21 | |
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 : š„ Why Colin left his role as VP of Product at Looker to build a new BI tool š„ The Omni vision: reconciling enterprise BI governance with the flexibity of Excel and SQL š„Ā AI for Analysis (āchat with your dataā): what Omni did differently in its Semantic Layer to make it work š„Ā The future of Data teams when anyone can do complex analyses in minutes ā¤ļø SPONSOR This episode is made possible by Omni, the next-generation BI platform already used by many companies (Brevo, Photoroom, etc.). šĀ Discover the demos š RESOURCES - Jason Lemkinās SaaStr blog - Dave Kellogās Kellblog blog - Demos on the Omni website (Build in Public) š¬ CHAPTERS 00:00 Colinās career path 01:37 Omniās initial vision 05:07 From Looker to Omni 09:42 Why data leaders choose Omni 15:53 AI for Analysis (āChat with your dataā): what Omni did differently in its Semantic Layer to make it work 20:12 āBuilding in publicā at Omni 24:36 The evolution of data teams 30:58 The specifics of the French market 32:30 Colinās resource recommendations 33:13 What he likes most about data š§ 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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #3 - Aircall: Adapting the Data Strategy to the slowing economic environment | 03 Dec 2025 | 00:25:00 | |
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: š„ The overall economic context for scaleups: going from hyperscale to a slower controlled growth š„ His conviction that this context requires more centralisation rather than decentralisation (aka Data Mesh) š„ How centralisation enables more governance and control over costs and ressource management š„ The initiatives that they launched around 3 pillars: cost tracking, project structure and culture shift. š¬ 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 10:47Ā 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 20:00Ā Edouardās ressource recommendations 21:07 What he likes most about data 21:51Ā What made him improve the most 22:47 The best advice Edouard ever received š RESSOURCES - The book Trillion Dollar Coach - The article āThe Next Era of Data at Instacartā by Nate Kupp š§ 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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #2 - Deezer: How I restructured the Business Analytics team and made it more Business-Focused | 02 Dec 2025 | 00:32:43 | |
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 : š„ His career path to become Director of Operational Performance at Deezer, š„ The 4 pillars of his strategy: bring business focus, reorganize the team, retain talents and recruit the best, š„Ā His biggest difficulty: being patient and asking the other teams to be patient too, š„Ā His main advice when it comes to managing a team without any prior data experience. š¬ CHAPTERS 00:00 Trailer 01:14 Introduction 02:11 His career from Finance to Director of Operational Performance at Deezer 07:14 Thibaudās 1st strategy pillar: bring business focus in his team 10:49 Thibaudās 2nd strategy pillar: organize the Business Analytics team 15:12 Thibaudās 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 Thibaudās 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 š RESSOURCE š§ OTHER EPISODES #1 - BlaBlaCar : Managing 50 Data People with Manu, VP Data #3 - Aircall: Adapting the Data Strategy to the slowing economic environment š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||
| #1 - BlaBlaCar: Managing 50 Data People with Manu, VP Data | 01 Dec 2025 | 00:35:19 | |
Emmanuel Martin-Chave is VP Data at BlaBlaCar, the French unicorn who offers several mobility services. I had already welcomed him on the podcast to know more about their data strategy in the episode #13. This time, we talk about management. We address : š„Ā What the Data department looks like today š„ How to introduce āMiddle Managersā (Manu prefers āFront Line Managersā) š„ How to create a great path for Individual Contributors š„ Why itās crucial to anticipate recruitments 3 years in advance when youāre 50 in the team. š¬ CHAPTERS 00:00 Trailer 01:45 Intro 02:35 What the Data department looks like 03:38 Why and how to introduce middle managers? 07:51 The importance of having a mix between Individual Contributors (IC) & Managers 10:29 The current mix between IC & Managers at BlaBlaCar 13:22 The challenges associated with this organization 17:11 How to create a great path for IC 22:26 Why itās crucial to anticipate recruitments 3 years in advance when youāre 50 in the team 25:13 His main challenges in terms of management 29:18 The next steps of the Data team 30:34 Last questions (ressources, tipsā¦) š RESSOURCE An Elegant Puzzle by Will Larson š§ OTHER EPISODES #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 š SUPPORT THE PODCAST FOR FREE 1/ Subscribe š 2/ Leave a 5 stars review on Apple Podcasts here š„° Hosted on Acast. See acast.com/privacy for more information. | |||