About the job
At Doist, we aim to empower individuals with intuitive yet robust tools that enhance productivity.
We are a diverse and fully remote team dedicated to developing innovative products, such as Todoist and Twist, which significantly improve the way people work and live. Our mission revolves around finding fresh solutions to age-old productivity challenges and reimagining the creation of productivity tools.
Core Values
Our values are few but powerful. They guide our processes, decision-making, and recruitment, embedding meaning into our work.
- Ambition: You strive to make a significant impact. You maintain high standards for yourself and your peers, addressing challenges that greatly affect our customers and business.
- Mastery: You are committed to the excellence of your work, actively pursuing learning opportunities and pushing your limits. As a craftsman, you also prioritize your well-being by balancing intense work with complete disconnection.
- Independence: You are reliable in meeting deadlines and keeping commitments. You take initiative and ownership of your tasks, demonstrating accountability with minimal guidance.
- Communication: You communicate with clarity and engagement, keeping teammates informed and fostering positive relationships. You demonstrate cultural awareness and navigate social dynamics effectively.
Explore more about our philosophy, team, and workplace by visiting our blog.
Your Role & Team
We are seeking a versatile Data Engineer to become a key member of our Platform Engineering team at Doist. You will take the lead in managing our data infrastructure, creating pipelines, tools, and systems that transform raw data into insightful, actionable information for the entire organization.
While our products serve millions, our data infrastructure has grown organically and often relies on spreadsheets. We are at a pivotal moment to formalize our data strategy, redesign our architecture, conduct gap analyses to shape our roadmap, and enhance our data modeling and flows. You will prioritize use cases, identify the need for data pipelines, and empower teams with self-service analytics (aided by AI) without needing an engineer's intervention. Your contributions will be essential in driving this transformation.