Remote Data & Analytics Jobs
Data work suits remote teams well. Warehouses, notebooks and dashboards live in the cloud, and results are shared as written analysis. Remote data roles range from reporting and business analysis to large-scale data engineering and machine learning.
Latest remote data & analytics jobs
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Common remote roles
- Data analyst
- Answers business questions with SQL, spreadsheets and dashboards.
- Analytics engineer
- Models clean, tested datasets, often with dbt, so other teams can trust the numbers.
- Data engineer
- Builds the pipelines and infrastructure that move and store data.
- Data scientist / ML engineer
- Builds statistical models and machine-learning systems and puts them into production.
Skills employers ask for
- SQL fluency, plus Python or R for analysis
- A modern data stack: a cloud warehouse, dbt, orchestration tools and a BI tool
- Turning analysis into a clear written recommendation
- Data-quality and documentation habits that let others reuse your work
What these roles pay
Not enough published salary ranges yet. See salary insights.
Tips for applying
- Publish a small end-to-end project with a short write-up explaining the question, the method and what you found.
- In take-home tasks, explain your assumptions in writing. Reviewers check your reasoning as well as the result.
- Look for wording such as "US time zones" or "EMEA overlap" in the listing before you apply.
Frequently asked questions
What's the difference between a data analyst and a data scientist?
Analysts mostly explain what happened and why, using SQL and dashboards. Data scientists build predictive models and experiments. Job titles vary between companies, so read the responsibilities closely.