DataGen Europe

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🎬 CHAPTERS00:00 What's Tide?01:53 Tanmay’s journey05:39 Their main analytics projects08:19 Their stack10:50 His main challenges13:53 His career advice15:55 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 📹🎙 SUPPORT THE PODCAST FOR FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰

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🎬 CHAPTERS00:00 What's Marshmallow ?00:39 Ina's journey02:48 #1 - recruitment & stack10:23 #2 - better prioritization15:34 #3 - self-service & AI analytics21:55 #4 - AI project for customer support27:06 Their main challenges28:05 Their next steps30:04 The resources she recommends30:41 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🎙 SUPPORT THE PODCAST FOR FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰

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🎬 CHAPTERS00:00 What is Flix?02:38 Manoj's journey06:28 The Data team organization10:43 One of his main projects16:35 Their stack19:02 Their main challenges21:17 Their next step23:40 Resources he recommends24:42 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 FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰

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🎬 CHAPTERS00:00 What is HelloFresh?01:32 Florian’s journey from Data Analyst to Director of Product03:16 The context at HelloFresh when he became Director of Product05:49 #1 - How to define the metrics (North Star, KPI Tree…)08:30 #2 - How to manage product performance with data on a weekly basis12:17 #3 - How to implement the right collaboration between Product & Data15:38 His main challenges18:53 The tech stack he recommends21:04 The impact of GenAI on Product Analytics25:48 Florian’s favorite resources28:14 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 FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰

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🎬 CHAPTERS00:00 Introduction to N2603:25 How he became Head of Data for Marketing at N2610:49 1st project: implementing a Marketing Mix Model17:36 2nd project: building a User Value Model20:57 3rd project: Data Governance & Quality23:37 The data stack at N2625:16 The biggest challenges29:29 What’s next: decision automation31:11 Mathias’s favorite resources32:14 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 FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰

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❤️ SPONSORThis 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)🎬 CHAPTERS00:00 Colin’s career path01:37 Omni’s initial vision05:07 From Looker to Omni09:42 Why data leaders choose Omni15:53 AI for Analysis (”Chat with your data”): what Omni did differently in its Semantic Layer to make it work20:12 “Building in public” at Omni24:36 The evolution of data teams30:58 The specifics of the French market32:30 Colin’s resource recommendations33:13 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 FREE1/ Subscribe 🔔2/ Leave a 5 stars review on Apple Podcasts here 🥰