ABOUT THE TALK: When Taylor Murphy joined GitLab, they had just raised their Series C, had about 200 people, and he was the only person "doing data." Over the next 3 years, the company would 6x its total headcount and be on target to IPO, which it did in 2021, all while the demand for data and insights grew exponentially. This talk will detail that growth journey with a particular focus on how they built the data culture across the organization. Taylor will share what went well and what he would repeat, and he'll be honest about what he would do differently if he could go back in time and do it all again.

ABOUT THE SPEAKER: Taylor Murphy is the Head of Product and Data at Meltano, an open source data platform that enables collaboration, efficiency, and visibility. Taylor has been deeply involved in leading and building data-informed teams his entire career.

At Concert Genetics he scaled the Data Operations team to enable the management of hundreds of thousands of genetic tests and millions of claims records.

At GitLab, he was the first data hire where he focused on building and scaling the data organization as the company headed towards its IPO.

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Julia just got back from Data Council in Austin, a conference organized by Pete Sonderling, where lots of startups share what they're building, data practitioners go to learn in hands-on workshops, and of course investors go to spot the next big trend. In this episode, Taylor Murphy (Head of Product & Data at Meltano) + Pedram Navid (Founder, West Marin Data) join Julia to recap the conference and have a bit of fun. They talked streaming, how the MDS is growing up, new SQL variants, and, of course, AI. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com.

Summary Data integration in the form of extract and load is the critical first step of every data project. There are a large number of commercial and open source projects that offer that capability but it is still far from being a solved problem. One of the most promising community efforts is that of the Singer ecosystem, but it has been plagued by inconsistent quality and design of plugins. In this episode the members of the Meltano project share the work they are doing to improve the discovery, quality, and capabilities of Singer taps and targets. They explain their work on the Meltano Hub and the Singer SDK and their long term goals for the Singer community.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch. Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Your host is Tobias Macey and today I’m interviewing Douwe Maan, Taylor Murphy, and AJ Steers about their work to level up the Singer ecosystem through projects like Meltano Hub and the Singer SDK

Interview

Introduction How did you get involved in the area of data management? Can you start by describing what the Singer ecosystem is? What are the current weak points/challenges in the ecosystem? What is the current role of the Meltano project/community within the ecosystem?

What are the projects and activities related to Singer that you are focused on?

What are the main goals of the Meltano Hub?

What criteria are you using to determine which projects to include in the hub? Why is the number of targets so small? What additional functionality do you have planned for the hub?

What functionality does the SDK provide?

How does the presence of the SDK make it easier to write taps/targets? What do you believe the long-term impacts of the SDK on the overall availability and quality of plugins will be?

Now that you have spun out your own business and raised funding, how does that influence the priorities and focus of your work?

How do you hope to productize what you have built at Meltano?

What are the most interesting, innovative, or unexpected ways that you have seen Meltano and Singer plugins used? What are

Data teams can significantly improve their stature and abilities in an organization, when they work with a product mindset. Product teams typically have UX experts, Designers, Product Managers, Engineering Managers and more, involved in the process of generating new features that will delight their customers.

In this video, we'll argue that Data teams should take on a very similar mindset when leading and growing their data org. We'll make the case that this mindset can scale from a single person team to a large organization. We'll share what this looks like on the ground and in the day to day.

Viewers will be able to walk away feeling empowered about the vital role the data team should — and can — play in every organization. They will explore a new mental framework for how to think about all of the data related activities in their organization.