Overview
At Doist, our mission is to empower people with simple yet powerful tools. We are a multidisciplinary, fully-remote team, passionate about creating products like Todoist and Twist that improve people's lives. We seek to rethink how productivity tools are made and thrive on innovating new solutions to old productivity challenges.
Your Team & Role
We are looking for a generalist Data Engineer to join the Platform Engineering team at Doist. You'll be the primary technical owner of our data infrastructure — building pipelines, tools, and systems that turn raw data into actionable insights for the whole company.
Our products serve millions of users, but the data infrastructure is rudimentary. We are formalizing our data strategy, rethinking data architecture, performing gap analysis to drive a roadmap, reviewing data modeling and data flows, qualifying data consumption needs, prioritizing use cases, identifying the need for data pipelines, and enabling teams to answer their own questions (with some AI assistance) without needing an engineer. You'll be central to that transformation.
The Platform team owns the data infrastructure; other teams own reporting, and Product owns experiments — you'll work at the intersection of all three, central to the value creation flywheel.
You will:
* Build and maintain data pipelines from OLTP production systems (MySQL, ClickHouse) to a data lakehouse/warehouse.
* Design and implement CDC (Change Data Capture) solutions — our current pipeline is stale and needs replacement.
* Own data quality — set up monitoring and alerting to the relevant teams responsible for the systems collecting the data, and ensure freshness across our data and analytics infrastructure.
* Enable self-serve analytics — help engineers and non-engineers answer their own questions without needing an engineer.
* Document and democratize — help maintain and refine tooling for data catalogs, metric definitions, and make data discoverable.
* Platform Engineering — contribute to other Platform Engineering challenges, helping accelerate other teams while upkeeping reliability and confidence.
This is a 70% data / 30% platform role. You'll spend most of your time on data engineering, but you'll also contribute to the broader Platform mission.
Why This Role Exists
Doist has grown to serve millions of users, but our data capabilities haven't scaled accordingly:
* Knowledge is concentrated — too few people know how our rudimentary data systems work.
* Pipelines are unreliable — our MySQL CDC pipeline has been unreliable and needs to be rebuilt.
* Self-serve is blocked — non-engineers need engineers to answer basic questions about their own data.
* No governance for analytical systems — our retention and privacy policies focus on OLTP and need to apply to the new data systems you'll be responsible for before data access becomes democratized.
This role addresses all four. You'll bring expertise, rebuild reliability, enable self-serve, and help establish governance.
About the Team
You'll join the Platform team, a small group focused on the infrastructure and systems that power Doist. We own databases, cloud infrastructure, some developer tooling, and, with this hire, data systems.
You'll report to the Head of Platform and work closely with:
* Finance — who owns company metrics and dashboards
* Product — who owns feature metrics and experiments
* Backend — who owns in-product data collection
The team values:
* Async-first communication
* Ownership and autonomy
* Shipping iteratively
* Building for the long term
Here are core things we believe will set you up for success in this role:
Technical Skills
* Systems programming — proficiency in Go or Rust for building performant, reliable data tooling. Knowledge of memory management, concurrency, and scalable software design.
* Linux systems knowledge — identify I/O bottlenecks, interpret OS performance metrics, and debug performance issues at the OS level.
* Strong SQL — write, optimize, and debug queries against messy historical data.
* Low-level data formats — experience with Parquet, Iceberg, columnar storage tradeoffs, and lakehouse architectures.
* Data warehouse/lakehouse experience — BigQuery, Snowflake, Redshift, or similar.
* Cloud platforms — AWS required (S3, Glue, Athena, RDS); GCP familiarity a plus.
* Pipeline tooling — experience with CDC, orchestration, or streaming systems (e.g., Debezium, Airflow, Kafka, Kinesis).
* Data modeling — dimensional modeling, schema design, OLTP vs OLAP tradeoffs, evolving schemas without breaking downstream consumers.
* Integrations — ability to build end-to-end data ingestion from 3rd parties using APIs and webhook handlers.
Mindset
* Translate business questions into technical requirements — turn vague questions into concrete data problems.
* Comfort with imperfect historical data and evolving schemas — pragmatic approaches to make sense of it.
* Data quality and availability — a pipeline with wrong data is worse than none.
* Simple, cost-efficient solutions — prefer straightforward, working solutions over complex ones.
* Independent work in a remote, async-first environment.
* Comfort with ambiguity — clarify requirements as needed.
* Document as you go — ensure that work is understandable by others.
* Leverage AI tools effectively — use AI to accelerate work while applying judgment to validate outputs.
Nice to Have
* Infrastructure-as-code (Terraform, CloudFormation)
* Analytics engineering (dbt)
* Python scripting for glue code and automation
* Data observability tools
* Experience with data governance and privacy controls
Apply soonest, as these roles don't come along often and we move fast.
Our Process
* Submit your complete application by March 23, 14:00 UTC. Attach a resume and thoughtful responses to all questions. No cover letter needed.
* Application screening. We review every application to understand your motivation, skills, and experience. You'll receive a response regarding the status of your application.
* Salary transparency & Value-alignment interview with shortlisted candidates. If shortlisted, we'll share the salary range for your location up front and then schedule a call with the CTO.
* Paid Task Assignment. Demonstrate role-specific skills, reasoning, and approach.
* Role-alignment panel interview with the Head of Platform Engineering.
* Culture-contribution interview with a Platform Engineer.
* Reference & Background checks.
* Offer to the successful hire.
Our perks and benefits are designed to provide the freedom and support you need to grow personally and professionally. Here's what that looks like:
The basics
* We work remotely and mostly async from anywhere. If a location is advertised, apply as usual; this is often due to board restrictions.
* Design your own schedule. Doisters are encouraged to work 8-hour days and no more than 40 hours/week.
* Competitive pay. Salaries are based on skills and location.
Expand your professional skills
* Continue your education with a recurring budget for conferences, courses, and books.
* Collaborate in person at retreats.
Craft your ideal work environment
* Cozy a coworking space with a monthly stipend.
* Budget for home internet and work apps.
* Purchase the hardware you need with a recurring budget.
Focus on your well-being
* 8 weeks (40 days) of vacation per year.
* Paid parental leave and pregnancy-related leave.
* Monthly wellness budget for health-related needs.
Note: We communicate from @doist.com emails and provide application details on doist.com/careers. For questions, contact careers@doist.com.
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