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The unified platform for proactive data quality
At Datafold, we build tools for data practitioners to automate the most error-prone and time-consuming parts of the data engineering workflow: testing data to guarantee its quality.
We are an all-remote team of global data lovers
We empower data teams to build reliable data products faster
While data quality (just like software quality) is a complex and multifaceted problem, we draw from decades of our team’s combined experience in the data domain to build opinionated tools our users love. Specifically, we believe that:
That means, rather than building yet-another-app for data practitioners to switch to and from, we insert our tools in the existing workflows, for example, in CI/CD for deployment testing and IDEs for testing during development.
Most data quality issues are bugs in the code that processes data, and applying a proactive, shift-left approach is the most effective way to achieve high shipping velocity and data quality simultaneously.
We bring powerful tools such as data diffing and column-level lineage to every data engineer’s workflow to help them validate the code and underlying data and fully understand the dependencies in complex data pipelines.
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We are here to make a positive dent in the world by doing the best work of our careers, share a great upside at some point and enjoy the journey throughout.
So far we've had all stars align in our favor, and the only reason why we wouldn’t succeed if we don’t execute it well enough or fast enough.
Your contribution to our shared success – your impact on our users, the team, product and company is ultimately what matters.
We work across time zones and cultures and rely primarily on asynchronous interactions. This requires intention in how we communicate and make decisions.
Don’t expect things to happen naturally or the information flow organically. Act with intent.
When you have a plan or idea or spot something broken, bias toward action. Build it, improve it, fix it.
Most decisions are reversible. Taking two steps forward and one back is better than not stepping forward at all.
Ship early and often. Quality ≠ perfection. We strive for high-quality impact, but there is no impact (and often, no learnings) until someone is using it.
If you are stuck, reach out for help. Be the primary driver for solving your problem and involve others.
It’s ok to step on toes. We value impact, not fitness to the job title. If you, however, do happen to step on someone’s toes, be respectful, considerate and kind.
Take extreme ownership: when things go wrong, bias toward taking responsibility. When it seems that it’s someone else’s fault, ask yourself: what could you have done to help them do the right thing? Then do it.
Treat recruiting including interviewing and convincing candidates to join our team at least as important as whatever you do as part of your role.
Datafold exists to empower data and analytics engineers. The work that doesn’t eventually translate into creating value for our users has no purpose.
Empowering your team members by helping them acquire important context and learn, by reviewing their work and discussing ideas is a great way to make impact.
Empower your team by moving up the stack and automating your role away. Create processes, tools, and documentation. There is no honor in being irreplaceable but there is in being invaluable. By enabling others on the team to help themselves and automating your routine tasks, you gain leverage to create ever more value.
In a remote, async, cross-timezone setting, it’s ok to repeat yourself multiple times to drive alignment. Be creative, patient and persistent in communication: sometimes it’s helpful to jump on a quick call, sometimes you need to think about improving docs and pinning something to a Slack channel.
Highlighting your progress, celebrating success helps others learn from you and boosts morale. Floating up challenges lets others help you out and builds trust.
Give a hand, don’t let your teammates fail. We are playing a long game in tough times.
Be generous when giving positive feedback, be brave and vulnerable when giving negative feedback to help someone improve. Positive feedback can have strong positive ripple effects if given in public, e.g. in #thanks Slack channel. Negative feedback should be given in private.
In a remote, cross-cultural setting and amidst all the pressure, it’s really easy to go down the spiral of taking things personally, and the results can be devastating. Assuming positive intent means that when an offense is taken, assume the person on the other side means well even if they haven’t communicated it in the exact way you’d wanted to. Offer feedback and use it as an opportunity to grow. If that doesn’t work, the behavior is egregious and/or violates our Code of Conduct, reach out your manager or the founders for help.
Work done well is its own end. Raise the bar for yourself and keep it high for others.
Startup=growth. We only succeed if we grow fast which requires a lot of leverage. Well-functioning and high-performing team of great people is our highest leverage. Company doesn’t grow without the growth of an individual. Improve, learn, and take feedback with gratitude and consider it as a great opportunity to grow.
We value the individual’s growth curve’s slope (i.e. how fast someone has been growing and learning) more than y-intercept (how accomplished they are by now) when hiring and evaluating performance.
There is no place for sloppiness. Our customers trust us with their most sensitive asset – data. Sloppiness is unacceptable for it’s destructive. Our users perceive it as indifference, and it deteriorates the culture and the morale of the team.
We move fast and occasionally break things. It’s ok to make mistakes, it’s not acceptable not to learn from them. Every major incident (not only in engineering) deserves a blameless post-mortem with lessons learned and shared across the larger team.
Take care of yourself. Working yourself to the bone is bad for you and bad for the team. Knowing what drains you, what gives your energy, and how to balance those is a great skill itself.
Backed by world-class partners
Datafold is used by data teams at Patreon, Thumbtack, Substack, Angellist, among others, and raised $22M from YC, NEA & Amplify Partners.
