Structuring data teams, the next big challenge for data, data as a product, jobs in data dream teams and more

Last week felt like "Metadata" took a whole new meaning! With Facebook starting its metaverse journey, the internet was filled with a flurry of new memes. And just 24 hours before that I was thinking about a name for this newsletter...

So, I'm going to go with it and introduce Metadata Weekly... a weekly newsletter covering range of topics including the latest from the data world, the modern data stack, metadata and most importantly, interesting memes!

? Spotlight: Structuring Your Data Team

Almost, every data leader I have spoken to has struggled with the "centralisation" vs "decentralisation" debate. I think Postman has a neat solution which I think can work well for data teams that are < 50 people. I wrote about in an in-depth article about how Postman structure their data team here.?

TL;DR: When Postman start hiring directly into decentralised teams?(e.g. marketing, sales, etc), they ran into some challenges! The decentralized analysts started building their own data systems and reporting metrics to their team manager.?Meanwhile, the central data team had their own data systems and metrics. This led to a ton of duplication of effort. After experimenting with decentralization, Postman has moved towards a more centralized data team. They hire analysts into the Data Science Team and train them centrally. After a several month onboarding process, some new hires move to the more data-mature teams (like the Product Team) as embedded or decentralized analysts.

I think there's a LOT to learn from Postman's thoughtful way of building a data team and culture and I'd recommend this to any data leader just starting up in a Series A - Series C startup.

?? Fave Links for This Week

• {Blog} The Next Big Challenge for Data is Organizational by Bryan Offutt:

"Software engineers have built some truly incredible tooling for making the process of developing software extraordinarily efficient and fault tolerant over the years. This is widely talked about, but only tells part of the story. What is?not?as widely talked about is the incredible?organizational?systems that software engineers have developed to facilitate the same efficiency."

Software teams are very different from data teams in a few different ways: (1) code is created by humans while data is created by systems that data teams don't always have control over, (2) a lot of data work is "science" and exploration oriented compared to engineering. That being said, I still think there's a lot we can learn from software engineering teams in building more specialisation & career paths in data teams.

• {Video} Data Is a Product: What Keeps Us From Managing It Like One?

Eric Weber gave a fantastic talk at Future Data 2021. I personally am very bullish about the concepts of treating data as a product which will allow us to treat consumers as "users", focus on experience & adoption and build reusable and well documented work.

• {Tweet Thread} Data Stack as a Code by Sarah Krasnik

2020 has seen more tools added to the data stack than ever before. Sarah writes, "There will be a world in which open source Terraform modules will define end to end data stacks no matter your vendor of choice, enabling data teams to spin up infra easily and repeatedly. Data teams should be given the time to think high level."

ICYMI: I save all my favourite articles and reads about the Modern Data Stack on my Notion here. Check out what I've been reading this month!

?? Work at a (Modern) Data Dream Team!

I truly believe that data dream teams will change the world, and I'm hoping to use this newsletter as a way to throw the spotlight on amazing teams that are adopting the best tooling (ahem... the modern data stack) and cultural rituals that make them amazing to work at.

• Jonathan?and the team at?Heap?are hiring their first?Senior Analytics Engineer?(remote) to help define the company's data architecture and build the BI infrastructure.
• Jordan?and the Data Team of?Education Analytics?are looking for an?Analytics Engineer/Data Engineer?(based in Madison, Wisconsin) to lead the design, build, and maintenance of data pipelines and analytic systems. They're also doing some amazing mission driven work to improve learning outcomes in students!
• David?from?Togo Group?is looking for a?Senior Data Product Manager?(based in the US) to help power up their analytics and data platform. I think Data Product Managers are soon going to replace Data Scientists as the sexiest job in the 21st century: and this is the best time to shape the future of the industry!

There are a lot of super interesting jobs open in amazing data teams! Check out some of the best roles out there in this weekly list curated by my partner in crime Surendran here.

Stay tuned till I come back next Tuesday with more interesting stuff around modern data stack. Meanwhile, follow the usual drill... like, share, subscribe. ;)

P.S: Obviously, I'd love feedback on what you'd like to see. You can also connect with me on LinkedIn here.