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The Firebolt Data Bros

The Data Engineering Show

A Technology , Business and Management podcast

#83 in Technology · 🇳🇬
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About the show

The Data Engineering Show is a podcast for data engineering and BI practitioners to go beyond theory. Learn from the biggest influencers in tech about their practical day-to-day data challenges and solutions in a casual and fun setting. SEASON 1 DATA BROS Eldad and Boaz Farkash shared the same stuffed toys growing up as well as a big passion for data. After founding Sisense and building it to become a high-growth analytics unicorn, they moved on to their next venture, Firebolt, a leading high-performance cloud data warehouse. SEASON 2 DATA BROS In season 2 Eldad adopted a brilliant new little brother, and with their shared love for query processing, the connection was immediate. After excelling in his MS, Computer Science degree, Benjamin Wagner joined Firebolt to lead its query processing team and is a rising star in the data space. For inquiries contact tamar@firebolt.io Website: https://www.firebolt.io

Newest episodes

How AI Is Reshaping Modern Data Teams and the Future of Platforms with Xavier Gumara Rigol

17 min

What if AI could transform how your entire data team works—without replacing them? In this episode, Benjamin Wagner explores with Xavier Gumara Rigol, Head of Data at Manychat, how natural language-to-SQL tools are reshaping data analyst and data scientist roles, why building a strong data platform is essential for AI-powered self-serve analytics, and the critical strategies for evaluating text-to-insight solutions in 2026. Whether you're leading a data organization or building your next analytics capability, discover how to balance build versus buy decisions and position your team for the AI-driven future of data engineering.

Building Modern Data Platforms Without Legacy Bottlenecks ft Andrew Jones

19 min

What if you could transform your data team from a bottleneck into a self-serve platform that empowers the entire organization? In this episode, host Benjamin Wagner sits down with Andrew Jones, Staff Data Engineer at LocalStack, to explore how to balance building new data infrastructure while supporting legacy systems, why reliability and data contracts are becoming non-negotiable, and how AI agents are accelerating platform development. Whether you're scaling a data organization or rethinking your data governance strategy, this conversation is packed with practical insights on managing different user personas, automating support requests, and staying open-minded as the data landscape evolves. Tune in to discover how to build resilient, self-serve data platforms that drive real business impact.

Why 99% of BI Tools Get Embedded Analytics Wrong And How Omni Fixed It ft. Chris Merrick

20 min

What if the future of analytics wasn't about building another middleware layer, but about getting closer to the actual business user? In this episode, Benjamin sits down with Chris Merrick, CTO and cofounder of Omni, to explore why semantic layers matter more than ever in an agentic world, how AI is reshaping embedded analytics and customer-facing data experiences, and the key strategies for keeping complex data models aligned across federated sources. Whether you're building analytics platforms, managing data infrastructure, or trying to make AI work at scale, this conversation is packed with practical insights on balancing governed analytics with exploratory AI, unifying disparate data sources, and capturing business intelligence beyond just the metrics in your warehouse. Tune in to discover how the next generation of analytics platforms will need to think about the entire business, not just the data.

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All episodes

How AI Is Reshaping Modern Data Teams and the Future of Platforms with Xavier Gumara Rigol

17 min

What if AI could transform how your entire data team works—without replacing them? In this episode, Benjamin Wagner explores with Xavier Gumara Rigol, Head of Data at Manychat, how natural language-to-SQL tools are reshaping data analyst and data scientist roles, why building a strong data platform is essential for AI-powered self-serve analytics, and the critical strategies for evaluating text-to-insight solutions in 2026. Whether you're leading a data organization or building your next analytics capability, discover how to balance build versus buy decisions and position your team for the AI-driven future of data engineering.

Building Modern Data Platforms Without Legacy Bottlenecks ft Andrew Jones

19 min

What if you could transform your data team from a bottleneck into a self-serve platform that empowers the entire organization? In this episode, host Benjamin Wagner sits down with Andrew Jones, Staff Data Engineer at LocalStack, to explore how to balance building new data infrastructure while supporting legacy systems, why reliability and data contracts are becoming non-negotiable, and how AI agents are accelerating platform development. Whether you're scaling a data organization or rethinking your data governance strategy, this conversation is packed with practical insights on managing different user personas, automating support requests, and staying open-minded as the data landscape evolves. Tune in to discover how to build resilient, self-serve data platforms that drive real business impact.

Why 99% of BI Tools Get Embedded Analytics Wrong And How Omni Fixed It ft. Chris Merrick

20 min

What if the future of analytics wasn't about building another middleware layer, but about getting closer to the actual business user? In this episode, Benjamin sits down with Chris Merrick, CTO and cofounder of Omni, to explore why semantic layers matter more than ever in an agentic world, how AI is reshaping embedded analytics and customer-facing data experiences, and the key strategies for keeping complex data models aligned across federated sources. Whether you're building analytics platforms, managing data infrastructure, or trying to make AI work at scale, this conversation is packed with practical insights on balancing governed analytics with exploratory AI, unifying disparate data sources, and capturing business intelligence beyond just the metrics in your warehouse. Tune in to discover how the next generation of analytics platforms will need to think about the entire business, not just the data.

AI for Data and Data for AI: The Dual Frontier of Modern Data Engineering with Pranav Motarwar

19 min

What if the data engineering skills you have today become obsolete in five years? In this episode, host Benjamin Wagner sits down with Pranav Motarwar, a data engineer who's witnessed the industry's transformation from traditional ETL to AI-powered pipelines, to explore how AI is fundamentally reshaping data engineering roles, why you need to master both "AI for data" and "data for AI" to stay relevant, and the emerging infrastructure required to handle multimodal data at scale. Whether you're a data engineer wondering about your career longevity or a builder curious about next-gen data stacks, this conversation unpacks the skills you'll need, the tools defining 2026, and why data engineers aren't disappearing - they're just evolving faster than ever.

AI Won't Replace Engineers, But This Framework Will Change How They Build with Rohit Girme

18 min

What if you could build AI features with confidence while moving at the pace of innovation? In this episode, Benjamin Wagner sits down with Rohit Girma, Staff Software Engineer at Airbnb, to explore how to evaluate generative AI in production, why breaking down complex problems into smaller chunks accelerates development, and the key strategies for scaling AI-powered products beyond zero-to-one. Whether you're shipping AI features or transforming your engineering workflow, this conversation offers practical insights on building reliable AI systems, leveraging LLMs as orchestration tools, and the future of software development. Tune in to discover why humans remain essential in the scaling phase and how your team can move faster without sacrificing quality.

The Framework Canva Uses for 200M+ Designers with Paul Tune

22 min

In this episode of The Data Engineering Show, Benjamin sits down with Paul Tune, Staff Research Scientist at Canva, to explore the advancement of machine learning at one of the world's leading design platforms. Learn how Canva is transitioning from traditional ML like recommendation engines for templates to cutting-edge agentic workflows that allow users and AI to collaborate on complex design tasks. Whether you're interested in the infrastructure behind distributed training or the nuances of post-training LLMs for aesthetic tasks, this deep dive offers a masterclass in scaling ML for millions of creative users.

Llama 2 & 3 Safety: Soumya Batra on Agentic AI Training

22 min

What if the expertise that built foundation models could reshape how you think about AI's future? In this episode, Benjamin sits down with Soumya Batra, founder and CEO of WisePort AI and former safety lead on Llama 2 and Llama 3 at Meta, to explore how foundation models evolved from traditional NLP, why post-training holds the highest leverage for safety and controllability, and what natively agentic AI means for the next frontier of AI development. Whether you're curious about the model training lifecycle or wondering what comes after large language models, this conversation unpacks the technical strategies and vision shaping tomorrow's AI systems.

The Data Fusion Secret & Why Custom Query Engines Fail with Nikita Lapkov

18 min

What if building a distributed SQL engine meant rethinking everything about how query execution works at scale? In this episode, Benjamin sits down with Nikita, Senior Software Engineer at Cloudflare, to explore how R2 SQL leverages object storage and distributed computing to power analytics across 300 global locations, why backward compatibility becomes critical when you can't control infrastructure rollouts, and the key strategies for handling joins and adaptive query execution in a stateless, point-to-point network architecture. Whether you're designing distributed systems or curious about how Cloudflare processes petabytes of data, this conversation reveals the real-world engineering challenges and innovations shaping the future of cloud data platforms.

How Zipline AI Turns Weeks of Engineering Into Minutes of SQL Queries ft. Nikhil Simha

24 min

What if you could deploy ML features and real-time data pipelines without building complex infrastructure from scratch? In this episode, host Benjamin sits down with Nikhil Simha, CTO at Zipline AI and co-author of Chronon AI, to explore how Chronon, an open-source system that generates data infrastructure from simple queries, is transforming feature engineering at companies like OpenAI and Airbnb. Learn why iteration speed matters for fraud detection, how to serve thousands of signals at a massive scale, and what the future of analytical databases looks like in an AI-first world. Whether you're scaling real-time ML systems or building customer-facing analytics, this conversation is packed with practical insights on bridging the gap between data scientists and ML engineers.

The Geo-Data Problem Nobody Talks About And How Voi Solved It ft. Magnus Dahlbäck

16 min

What if your data platform could power both critical business decisions and real-time product features at scale? In this episode, host Benjamin sits down with Magnus Dahlbäck, Senior Director of Data and Platform at Voi, to explore how a metrics-first approach and semantic layers transform data accessibility, why traditional ML and LLMs require different strategies for different problems, and how to balance FinOps costs while processing billions of IoT events daily. Whether you're building data infrastructure for a high-growth company or rethinking how your organization consumes data, this conversation is packed with practical strategies for unlocking data value and preparing your platform for AI. Tune in to discover how Voi ditched traditional BI tools and revolutionized their approach to enterprise analytics.

Why 99% of Data Teams Give Up on Real-Time And How Artie Changes That

29 min

What happens when a team of seven engineers spends a year trying to build a production-ready CDC connector and fails? For Artie CTO and co-founder Robin Tang, it was the spark needed to build a platform that makes data streaming accessible. In this episode, Robin joins Benjamin to discuss the "DFS" (Deep First Search) approach to data sources, the engineering hurdles of real-time Postgres-to-Snowflake pipelines, and why "theoretically correct" architectures often fail in practice.

The $100M Problem: How Lyft's Data Platform Prevents ML Failures with Ritesh Varyani at Lyft

25 min

What if your data platform could serve AI-native workloads while scaling reliably across your entire organization? In this episode, Benjamin sits down with Ritesh, Staff Engineer at Lyft, to explore how to build a unified data stack with Spark, Trino, and ClickHouse, why AI is reshaping infrastructure decisions, and the strategies powering one of the industry's most sophisticated data platforms. Whether you're architecting data systems at scale or integrating AI into your analytics workflow, this conversation delivers actionable insights into reliability, modernization, and the future of data engineering. Tune in to discover how Lyft is balancing open-source investments with cutting-edge AI capabilities to unlock better insights from data.

60 Billion Predictions Daily: Inside Credit Karma’s Agentic Data Layer with Maddie Daianu

19 min

What does MLOps look like when you are deploying 60 billion machine learning predictions a day? Maddie Daianu, Head of Data and AI at Intuit Credit Karma, joins the Data Bros to pull back the curtain on one of the most high-volume data environments in FinTech. With a 100-person team serving 140 million members, standard data practices break down. Maddie shares how her team manages terabytes of daily data on Google Cloud and explains the massive strategic pivot they are undertaking right now: The move from "Information" to "Agency."

Block Bad Data Before the Write with Nike’s Ashok Singamaneni

20 min

Nike’s Principal Data Engineer Ashok Singamaneni joins Benjamin and Eldad to discuss his open-source data quality framework, Spark Expectations. Ashok explains how the tool, which was inspired by Databricks DLT Expectations, shifts data quality checks to before the data is written to a final table. This proactive approach uses row-level, aggregation-level, and query data quality checks to fail jobs, drop bad records, or alert teams - ultimately saving huge costs on recompute and engineering effort in mission-critical data pipelines.

Postgres vs. Elasticsearch: The Unexpected Winner in High-Stakes Search for Instacart with Ankit Mittal

21 min

Modernizing Search Infrastructure: How Instacart Transitioned from Elasticsearch to PostgreSQL for Enhanced Performance and Simplicity. In this episode of The Data Engineering Show, host Benjamin Wagner speaks with Ankit Mittal, former senior engineer at Instacart, about the company's innovative approach to modernizing their search infrastructure by transitioning from Elasticsearch to PostgreSQL for single-retailer search functionality.

Is Self-Service BI a False Promise? Lei Tang of Fabi.ai Thinks So

21 min

AI is reshaping business intelligence by enabling true self-service analytics and transforming how organizations interact with their data through natural language processing. In this episode of The Data Engineering Show, host Benjamin interviews Lei, Co-founder and CTO of Fabi.ai, to explore how AI-native BI platforms are reshaping data analytics and empowering non-technical users to derive meaningful insights from complex datasets.

From Zero to 100M Users: Inside Notion’s Data Stack and AI Strategy with Sumit Gupta

22 min

Dive into the future of data engineering with Sumit Gupta, Lead BI Engineer at Notion, as he shares insights with the bros on navigating the AI revolution in modern data stacks. From leveraging tools like Snowflake and dbt to automating content creation with AI, discover how traditional technical skills are evolving alongside the rise of AI. Whether you're a seasoned data professional or just starting your journey, learn why embracing AI isn't optional and how to balance technical expertise with crucial soft skills in this rapidly changing landscape. Get an insider's perspective on working at tech giants like Notion, Snowflake, and Dropbox, while exploring practical applications of AI in both professional and personal contexts.

How Rising Wave Is Redefining Real-Time Data with Postgres Power

31 min

In this episode of The Data Engineering Show, the bros sit with Yingjun Wu, founder and CEO of Rising Wave, to explore the innovative world of stream processing systems. Yingjun shares his journey from academic research to creating a Postgres-compatible streaming system that drastically reduces resource usage. They discuss how Rising Wave's S3-based architecture and Postgres compatibility provide advantages over traditional systems like Flink, and explore the increasing role of Apache Iceberg in data pipelines.

Revolutionizing Data Governance with DataStrato’s Unified Open Source Approach

23 min

In this episode of The Data Engineering Show, the bros sit with Lisa Cao, Product Manager at DataStrato, to explore data catalogs and Apache Gravitino, a unified metadata lake used to manage access and perform data governance for all data sources. They discuss data catalogs and how they refine the data management process.

Database Technology in the Age of AI with DuckDB Labs co-creator Hannes Mühleisen

30 min

In this episode of The Data Engineering Show, the bros welcome the CEO DuckDB Labs and co-creator DuckDB, Hannes Mühleisen. They delve into the groundbreaking journey of DuckDB, an analytical database that processes billions of queries every month. Learn why DuckDB prioritizes broad compatibility over specialized optimizations, how its extension model works and the emerging solutions for database technology in the age of AI.

AI and Data Movement: Trends and Best Practices with Estuary’s Daniel Pálma

30 min

In this episode of The Data Engineering Show, the bros sit with Daniel Pálma, Head of Marketing at Estuary, to delve into the intriguing world of data engineering and marketing. Daniel shares his transition journey into marketing from data engineering and how his technical proficiency has been leveraged to market to engineers. The conversation cuts across the importance of AI in data movement, the future of data engineering, real-time data integration challenges, and the evolution of data integration.

AI and Data Change Management with Chad Sanderson, CEO Gable AI

36 min

In this episode of The Data Engineering Show, host Benjamin and co-host Eldad are joined by Chad Sanderson, CEO and co-founder of Gable AI to discuss the revolution of data quality and governance, the importance of understanding data flow and the processes that help organizations manage their data more effectively.

Tech Stacks and Tradeoffs: Xudo's Founder on Picking the Right Tools for BI Success

24 min

Wouter Trappers is the founder of Xudo and shares his slightly unconventional path from philosopher to data consultant with the Bros in this latest episode of The Data Engineering Show. Wouter’s grounding in philosophy has proved to be a shaping influence on his approach to business intelligence. Much more than just a software solution, for Wouter, BI is all about change management and aligning leadership with data projects.

Data Rewind: Conversation Highlights from Zach Wilson, Matthew Housley, Joe Reis, and Krishnan Viswanathan

28 min

This is a special episode of The Data Engineering Show, and joining the Bros is not one guest, nor even two – instead they’re revisiting the best bits from three different fascinating episodes. In each, they spotlight essential trends and lessons learned across the evolving data engineering landscape. From data observability to bridging academia with real-world practice, this episode covers perspectives on where data engineering is heading and why certain challenges persist.

The Resurgence of SQL: Insights from Ryanne Dolan from LinkedIn

32 min

In this episode of The Data Engineering Show, Ryanne Dolan from LinkedIn joins the Bros to discuss LinkedIn's Hoptimator project. Ryanne explains how they’re simplifying complex data workflows by automating them through SQL queries, integrating Kubernetes, Kafka, and Flink. The conversation highlights the shift towards a consumer-driven data model and the future of data engineering.

Vector Databases Won’t Replace SQL - Andy Pavlo

42 min

SQL’s slow. SQL’s stupid. We hear these claims every time a new shiny tool enters the market, only to realize five years later when the hype dies down that SQL is actually a good idea. In this super techie episode of the Data Engineering Show, Andy Pavlo, Associate Professor at Carnegie Mellon University, joins the bros to delve into database internals and optimization. Andy discusses leveraging ML for autonomous database optimization, using Postgres for practical applications, tuning production databases safely, and why SQL is here to stay.

How ZoomInfo transitioned from data graveyards to ROI-driven data projects

39 min

Too often expensive resources and manhours are spent on dashboards no one uses, resulting in zero ROI. Philip Philip Zelitchenko, VP of Data & Analytics at ZoomInfo met the bros to talk about adopting product management principles to ensure data projects have value, and provide an unfiltered peak into ZoomInfo’s data stack and unique tech culture. 

Joseph Machado, Senior Data Engineer @ LinkedIn talks best practices

25 min

Data engineering should be less about the stack and more about best practices. While tools may change, foundational principles will remain constant. Joseph Mercado, Senior Data Engineer at LinkedIn, is on The Data Engineering Show to talk about principles that are key to success, leveraging AI for automation, and adopting software engineering methods. 

Professors Joe Hellerstein and Joseph Gonzalez on LLMs

46 min

Joe Hellerstein is the Jim Gray Professor of Computer Science at Berkeley and Joseph Gonzalez is an Associate Professor in the Electrical Engineering and Computer Science department. They’ve inspired generations of database enthusiasts (including Benji and Eldad) and have come on the show to talk about all things LLM and RunLLM which they co-founded.If you consider yourself a hardcore engineer, this episode is for you.

Megan Lieu on powerful notebooks that enable collaboration

31 min

There are two types of data influencers on LinkedIn:1. Those who talk directly about the products and companies they work for2. Those that provide more general guidance, tips and opinions Can influencers actually be passionate about the products they’re developing and straightforwardly talk about them without sounding salesly? We’re kicking off 2024 with the amazing Megan Lieu on a new Data Engineering Show episode.Megan is one of those influencers that combine the two approaches, and with almost 100K followers, her content seems to be resonating with many data folks. She talked to the bros about her approach to data advocacy as well as the power of notebooks, especially when they become broader and enable collaboration.

Transitioning from software engineering to data engineering

29 min

Every data team should have at least one data engineer with a software engineering background. This time on The Data Engineering Show, Xiaoxu Gao is an inspiring Python and data engineering expert with 10.6K followers on Medium. She’s a data engineer at Adyen with a software engineering background, and she met the bros to talk about why both software and data engineering skills are so important.Without software engineering skills you’ll be limited to the rigid capabilities of your stack. But without data engineering skills you’ll find it hard to be cost effective and see the bigger picture.

Vin Vashishta explains why we should stop using dashboards

35 min

Vin Vashista, the guy we all love to follow, has never seen a dashboard with positive ROI. This time on The Data Engineering Show, he met the bros to talk about the difference between BI dashboards and analytics that actually introduce knowledge. It’s no longer just about the data volume, it’s about quality and relevance.

Joe Reis and Matt Housley on the fundamentals of data engineering

42 min

After co-writing the best-selling book ‘Fundamentals of Data Engineering’, Joe Reis and Matt Housely joined the bros for some much-needed ranting, priceless data advice, and good laughs. So why are we still talking about providing business value and dashboards, even though we don’t really have anything new to say? If there are so many great tools in the data stack, why are we still so troubled? How can we focus more on things like data governance and data quality that’ll actually push the industry forward?

Bill Inmon, the Godfather of Data Warehousing

30 min

As people in the data industry go, Bill Inmon is among the top, often seen as the godfather of the data warehouse. In this Data Engineering Show episode, Bill Inmon talks about surviving rabbit holes throughout the evolution of data, the data modeling renaissance, and why ChatGPT is not Textual ETL.

Large-scale data engineering at Momentive.ai - Meenal Iyer

38 min

As companies scale, data gets messy. The data team says one thing, the business team says something completely different. Meenal Iyer, VP Data at Momentive.ai, Met the Data Bros to talk about enforcing collaboration in large organizations to ensure what she considers the three most important data factors: Adoption, Trust, and Value.

Data engineering from the early 2000s till today - BlackRock

41 min

When it comes to data management, have we come a long way since the early 2000s? Or has it simply taken us 20 years to finally realize that you can’t scale properly without data modeling. With over 20 years of experience in the data space, leading engineering teams at Cisco, Oracle, Greenplum, and now as Sr. Director of Engineering at BlackRock, Krishnan Viswanathan talks about the data engineering challenges that existed two decades ago and still exist today.

Zach Wilson on what makes a great data engineer

34 min

How good you are at Spark or Flink ≠ how good you are at data engineering. After years of data engineering experience at Airbnb, Netflix, and Facebook, Zach Wilson is now focused on spreading the knowledge in EcZachly and all over social media. He met Benjamin Wagner to explain why data modeling and storytelling are more important than the actual tech, why data engineering is going to see more job growth than data science, and what brought him to start creating content, reaching over 250K followers on LinkedIn.

How ZipRecruiter and Yotpo power self-service data platforms that work

45 min

Data engineers are not paid to do support. Liran Yogev, Director of Engineering at ZipRecruiter, and Doron Porat, Director of Infrastructure at Yotpo talk about building resilient self-service products that keep customers happy and engineers calm. They walked the bros through their data stacks and explained how ZipRecruiter is completely rebuilding its data layer from scratch.

Data Observability with Millions of Users - Barr Moses

38 min

Barr Moses, CEO of Monte Carlo explains the difference between data quality and data observability, and how to make sure your data is accurate in a world where so many different teams are accessing it.

How Amplitude Engineers Process 5 Trillion Real-time Events

27 min

Weichen Wang, Senior Engineering Manager at Amplitude, came to meet the bros to talk about Amplitude's cutting-edge data stack and how it processes 5 Trillion real-time events while dealing with mutable data and massive scale.

Making Observability a Key Business Driver

48 min

80% of the code that you write doesn’t work on the first try. And that’s fine. But knowing which 80% is not working and which 20% is working is the actual challenge. After 10 years at Facebook, managing and scaling the Seattle site to over 6000 engineers(!) Vijaye Raji founded Statsig to make observability automated and real-time. How is the semantic layer managed? How was the Statsig team able to build an observability product that handles real-time ever-changing metadata? What are Vijaye’s main takeaways from engineering at Facebook? Tune in.

A ClickHouse Review from a Practitioner’s Point of View

34 min

Sudeep Kumar, Prinipal Engineer at Salesforce is a ClickHouse fan. He considers the shift to ClickHouse as one of his biggest accomplishments during his eBay days and walks Boaz through his experience with the platform. How on one hand it handled 2B events per minute, but also how it required rollups which compromised granularity when extending time windows. Besides a ClickHouse review from a practitioner’s point of view, Sudeep tells us about interesting use-cases he’s working on at Salesforce.

The Creator of Airflow About His Recipe for Smart Data-Driven Companies

45 min

According to Maxime Beauchemin, CEO & Founder at Preset and Creator of Apache Superset and Apache Airflow, building a thriving company is not so straight-forward. So how did he do it? Choosing the right system and services is key for a successful start, and can help you avoid the chaos of having too many tools spread across multiple teams. Max walks the Bros through his recipe for a smart data-driven company, and the genesis of Airflow, Superset & Presto (with some great tidbits about Airflow's old school marketing approach and how the open source platform took on a life of its own).

How Similarweb Delivers Customer Facing Analytics Over 100s of TBs

37 min

According to Yoav Shmaria, VP R&D Platform at Similarweb, the best way to manage data warehouse costs is tagging every table, database or ETL running to have good granularity over every feature. Besides handy cost management tips, Yoav walks the bros through the tech stack he implemented to analyze 100s of TBs of web data to serve fast customer-facing analytics. Full disclosure, Similarweb is a Firebolt customer, but the bros kept it objective, and there’s no Firebolt talk in this episode.

How Klarna Designed a New Data Platform in the Cloud

40 min

Klarna is one of the leading fintech companies in the world, valued at $45B. While many corporations are “stuck” on-prem, Klarna made the move and today is a cloud-only company. Gunnar Tangring, Klarna’s Lead Data Engineer tells Boaz what this new modernized stack looks like.

How Eventbrite is Modernizing its Data Stack

23 min

Archana Ganapathi, Head of Data & Analytics Engineering at Eventbrite, shares Eventbrite’s data stack modernization process, and how you get engineers to adopt new technologies like dbt which may be outside their comfort zone.

A Deep Dive into Slack's Data Architecture

34 min

Growing from a startup to an IPOed and then an acquired company meant that Slack’s sales org was scaling rapidly. Apun Hiran, Slack’s Director of Software Engineering explains how the data stack and architecture evolved to support this growth with more reliable and timely metrics. Speaker: Apun Hiran, Director of Software Engineering (Data), Slack Hosts: Eldad and Boaz Farkash, CEO and CPO, Firebolt

Transitioning Scopely’s 5.5 PB Data Platform to the Modern Data Stack

31 min

Should data engineering AND BI be handled by the same people? According to Jonathan Palmer, VP Data Platform at Scopely – YES. By Analytics Engineers. His team of Analytics Engineers is in the final stages of transitioning 5.5 PBs of data which include 15B evens per day to the modern data stack. Tune in to learn how they did it.

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