The Stacked Data Podcast

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The Stacked Data Podcast is a community for data professionals working with the modern data stack, machine learning, and AI. In each episode, we speak with data leaders who are building and scaling analytics, data platforms, and AI capabilities inside forward-thinking organisations. We explore how modern data teams operate, the technologies they use, and the lessons learned from building impactful data and AI products. The podcast is designed for Data Leaders, Data Engineers, Analytics Engineers, Analysts, and professionals working in Data Science, Machine Learning, or AI who want to stay close to the evolving world of modern data. The Stacked Data Podcast is organised by Cognify, the recruitment partner for modern data and AI teams. cognifysearch.comOmni.co

  1. 040 - Why Most AI Projects Fail (And How to Get Them Right)

    2 DAYS AGO ·  VIDEO

    040 - Why Most AI Projects Fail (And How to Get Them Right)

    In this episode of the Stacked Data Podcast, Harry sits down with Adam, Head of Analytics, Data & Engineering at MediaLab, to tackle one of the biggest gaps in the industry right now: Why so many AI projects never make it past experimentation — and what it actually takes to deliver real value. Adam has built a reputation as a pragmatic (and often sceptical) voice in the AI space. In this conversation, he breaks down what’s really driving the current wave of AI adoption — and why much of it is still fuelled by hype, not outcomes. They explore how to properly identify and validate high-value AI use cases before writing a single line of code, what “AI readiness” actually means beyond buzzwords, and how to think about testing, governance, and risk in production systems. A big theme throughout is the role of humans in the loop — why removing them too early creates more problems than it solves, and how the best teams design AI systems that augment, rather than replace, decision-making. Finally, Adam shares how to measure real impact and what it takes to scale beyond a single successful use case — turning AI from a side experiment into a meaningful business capability. If you’re a data leader or practitioner trying to cut through the noise and build AI that actually delivers, this episode is packed with practical frameworks and hard-earned lessons.

    48 min

  2. 25 MAR ·  VIDEO

    039 - The Data Science Identity Crisis

    The Data Science Identity Crisis | Anurag Gangal (Spotify) on Data Roles, Analytics Engineering & AI What does a data scientist actually do anymore? In this episode of the Stacked Data Podcast, Harry sits down with Anurag Gangal from Spotify to unpack one of the biggest challenges in modern data: the growing confusion around data role titles. From data scientists and analytics engineers to product analysts, machine learning engineers, and more, the data landscape has become increasingly hard to navigate. Anurag shares the story behind his framework for understanding data roles, why he built his now-popular quadrant model, and how it can help both companies and individuals make better decisions. The "Data Scientist" identity crisis - Anurag’s Substack They explore why so many businesses still use the title data scientist to describe completely different jobs, how that creates problems in hiring and team design, and what it means for people trying to build careers in data. The conversation also dives into generalists vs specialists, the evolution of the modern data stack, and how AI could reshape the future of analytics, data science, and self-serve data work. Whether you’re a data leader, analytics engineer, data analyst, product analyst, machine learning engineer, or someone trying to break into data, this episode will help you better understand where the industry is heading. In this episode, we cover: Why the term data scientist has become so confusing The difference between analytics engineers, data analysts, product analysts, and ML engineers How to think about specialisation vs generalisation in data teams The real cost of poorly defined data roles How Anurag’s data role quadrant model helps bring clarity How to think about your career path in data How AI may change the future of data science, analytics engineering, and self-serve analyticsGuest: Anurag Gangal, Spotify Host: Harry Gollop Podcast: Stacked Data Podcast If you enjoyed this episode, make sure to like, comment, and subscribe for more conversations with the people building the future of data.Our sponsor is Omni, an AI-powered BI platform that helps people use data to do their best work. Whether users prefer AI, Excel, point-and-click exploration, or SQL, Omni enables fast, trusted answers from a governed semantic model. The Stacked Data Podcast is produced by Cognify — a specialist recruitment partner for teams working across the modern data stack, machine learning & AI. If you’re looking to hire top data talent or exploring your next move in data, feel free to reach out to the Cognify team — we’re always happy to help and chat through the market. #DataScience #Spotify #AnalyticsEngineering #DataAnalytics #MachineLearning #DataCareers #ModernDataStack #AI #DataLeadership #ProductAnalytics #DataEngineer #Analytics #StackedDataPodcast

    46 min
  3. 038 - How Flo run 1500+ experiments a year to drive product development

    12/11/2025 ·  VIDEO

    038 - How Flo run 1500+ experiments a year to drive product development

    What does it take to run over 1,500 experiments a year — and still maintain speed, quality, and impact? In this episode, Harry sits down with Dmitry Zolotukhin, VP of Analytics at Flo, to unpack how one of the world’s leading health and wellness apps built a truly data-driven culture of experimentation.They explore Flo’s journey from early-stage testing to a mature experimentation framework, the technical infrastructure behind it, and how the team coordinates hundreds of tests at once without losing focus on user experience or business value. You’ll learn: How Flo scaled experimentation from small tests to 1,500+ annual experiments The tools and frameworks powering experimentation at scale Strategies for balancing speed vs. quality in testing How to foster a culture of learning and experimentation across teams Real examples of how data-driven insights shaped Flo’s product roadmap

    41 min
  4. 037 - Build vs Buy in the Modern Data Stack: Stories, Frameworks & Pitfalls

    29/10/2025 ·  VIDEO

    037 - Build vs Buy in the Modern Data Stack: Stories, Frameworks & Pitfalls

    On this episode of the Stacked Data Podcast, Harry Gollop sits down with Hugo Lu, co-founder of Orchestra, to tackle one of the most common debates in modern data teams: should you build your own tools or buy off-the-shelf solutions? Hugo shares his experiences on both sides of the decision, practical frameworks for evaluating cost, opportunity, and long-term value, and real-world examples of when building or buying was the right call. Whether you’re a Head of Data, an engineer, or just curious about tooling strategy, this episode provides actionable insights to help your team make smarter, strategic decisions.

    37 min
  5. 036 - From Meta to Statsig: Driving Business Impact Through Experimentation

    15/10/2025 ·  VIDEO

    036 - From Meta to Statsig: Driving Business Impact Through Experimentation

    This week, I’m joined by Timothy Chan, Head of Data at Statsig. Tim has a fascinating background — he started his career as a scientist developing life-saving drugs before pivoting into data. He went on to become a Staff Data Scientist at Meta and now leads the data function at Statsig, one of the world’s leading experimentation platforms, recently acquired by OpenAI. In this episode, we dive into the power of experimentation and how Meta embedded it into every aspect of product development. We unpack:⚙️ What great experimentation really looks like🏗️ How to build a world-class experimentation function💬 How data teams can use experimentation to influence business decisions⚖️ The balance between speed, rigour, and impact👥 Why stakeholder collaboration is the true differentiator of high-performing data teams Tim shares brilliant insights from his time at both Meta and Statsig — including how to think about experimentation as a cultural capability, not just a technical one. If you care about driving real business impact with data, this is a must-listen.

    47 min
  6. 035 - How to Be a Strategic Driver of the Business - Senior Director of Wise

    18/06/2025 ·  VIDEO

    035 - How to Be a Strategic Driver of the Business - Senior Director of Wise

    Welcome back to the Stacked Data Podcast — where we explore what it really takes to build impactful data teams in the modern world. This week’s episode is all about stepping out of the ticket queue and into the strategic driver seat. I sat down with Adam Cassar, Director of Analytics at Wise, to explore how analytics teams can break free from the reactive reporting cycle and become genuine business partners. This conversation is packed with real-life examples, practical strategies, and hard-earned lessons from Adam’s experience leading high-performing teams. We cover: ✅Why many analytics teams end up in a service-provider role — and how to shift that perception ✅The biggest barriers to becoming more strategic (and how to overcome them) ✅How to proactively influence business decisions (not just report on them) ✅What skills, mindsets, and relationships actually matter if you want your team to have impact Whether you're an IC or leading a data team, this episode is for anyone who wants to stop being a dashboard factory — and start driving real change in the business. 🔁Share it with someone who’s ready to level up their data career #StackedDataPodcast #AnalyticsEngineering #ModernDataTeam #DataLeadership #Wise #DataStrategy

    41 min
  7. 034 - Beyond the pipeline - Tracking the true impact of Analytics Engineering

    28/05/2025 ·  VIDEO

    034 - Beyond the pipeline - Tracking the true impact of Analytics Engineering

    𝐁𝐞𝐲𝐨𝐧𝐝 𝐭𝐡𝐞 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 – 𝐓𝐫𝐚𝐜𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 𝐓𝐫𝐮𝐞 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐟 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Analytics Engineering has become one of the most in-demand roles for modern data teams in recent years.  The role goes far beyond just building clean data pipelines and data models, but how do we actually measure that impact? In today’s episode of the Stacked Data Podcast, we're joined by Ross Helenius, Director of Analytics Engineering & AI Transformation Engineering at Mimecast, to unpack one of the most important (and overlooked) questions in data: 👉 What does success look like for Analytics Engineering: beyond the technical? 𝚆̲𝚎̲ ̲𝚎̲𝚡̲𝚙̲𝚕̲𝚘̲𝚛̲𝚎̲:̲ ✅ The true role of Analytics Engineering in modern data teams ✅ Why measuring ROI is so hard and how  you can do this ✅ How to define and track impact beyond pipelines, models, and dashboards ✅ Practical KPIs and strategies to showcase business value ✅ Pitfalls to avoid when proving the value of your data function Ross brings deep experience from the intersection of data, engineering, and AI, and offers actionable insights for data leaders and practitioners alike. Whether you're leading a data team, building one, or looking to become a better AE this episode is packed with value.

    48 min
  8. 033 - Digestible, Defendable, Actionable – How to drive impact with Data

    14/05/2025 ·  VIDEO

    033 - Digestible, Defendable, Actionable – How to drive impact with Data

    Digestible. Defensible. Actionable.What does it really take to drive impact with data? Too often, analysts are left wondering:“Why didn’t anyone do anything with that insight?” This week on the Stacked Data Podcast, I’m joined by Sam Marks, Director of Analytics & Business Strategy at the Boston Bruins, to explore the gap between finding insights and driving action — and how to close it. Sam shares the Digestible, Defensible, Actionable framework he uses to turn analysis into outcomes, covering: ✅ What makes an insight digestible (and where analysts go wrong)✅ How to make your work defensible and credible✅ What separates an interesting insight from an actionable one✅ How to overcome inaction from stakeholders✅ Real-world examples of the framework in action This one’s packed with tactical advice for any data professional tired of their work getting stuck in slide decks.

    36 min
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About

The Stacked Data Podcast is a community for data professionals working with the modern data stack, machine learning, and AI. In each episode, we speak with data leaders who are building and scaling analytics, data platforms, and AI capabilities inside forward-thinking organisations. We explore how modern data teams operate, the technologies they use, and the lessons learned from building impactful data and AI products. The podcast is designed for Data Leaders, Data Engineers, Analytics Engineers, Analysts, and professionals working in Data Science, Machine Learning, or AI who want to stay close to the evolving world of modern data. The Stacked Data Podcast is organised by Cognify, the recruitment partner for modern data and AI teams. cognifysearch.comOmni.co

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