Quick answer
Seattle tech job titles vary by company and do not always map cleanly across employers — Amazon’s "SDE" (Software Development Engineer) is roughly equivalent to "Software Engineer" elsewhere, "Applied Scientist" typically implies more research/ML-model focus than "Data Scientist," and "Data Engineer" (building data infrastructure) is a genuinely different role from "Data Analyst" (analyzing existing data). Always read the actual job description, not just the title, since usage varies by company.
Confusing or company-specific job titles make it harder to know which roles actually match your target track, especially for career switchers unfamiliar with the informal conventions of Seattle’s largest employers. This guide translates the most commonly confusing ones.
Common Seattle tech job titles, translated
| Title | What it usually means | Roughly equivalent to |
|---|---|---|
| SDE (Software Development Engineer) | Amazon’s standard software engineering title | "Software Engineer" at most other companies |
| Applied Scientist | Research and ML-model-focused role, often expecting an advanced degree | A specialized, research-leaning Data Scientist |
| Data Scientist | Broader mix of analysis, modeling, and business-facing work | Varies more by company than most titles on this list |
| Data Engineer | Builds and maintains data pipelines and infrastructure | A backend/infrastructure engineer focused specifically on data |
| Data Analyst | Analyzes existing, accessible data to answer business questions | The most business-facing of the data-track roles |
| Solutions Architect | Designs cloud infrastructure and technical solutions for specific use cases | A senior cloud engineering role with strong client/stakeholder-facing elements |
| DevOps Engineer | Builds and maintains deployment pipelines and infrastructure automation | Overlaps significantly with Cloud Engineer and Site Reliability Engineer titles |
How to use this when applying
- Always read the actual job description and responsibilities, not just the title — usage varies meaningfully by company.
- When a title is unfamiliar, search for it specifically at that company rather than assuming a universal definition.
- If a title seems to span two tracks you are considering (e.g. "Data Engineer" touching both cloud and data), that can be a genuinely good target if your skills bridge both.
A confusing title is not a reason to skip a role — it is a reason to read one paragraph further before deciding.
Where MITS Edge fits
MITS Edge’s Seattle tracks map directly to the roles covered above, with career mentorship to help translate between a track’s skills and the specific job titles you will encounter applying in Seattle.
Find the track that matches your target title.
Explore the Seattle pageFrequently asked questions
What does SDE mean at Amazon?+
SDE stands for Software Development Engineer, Amazon’s standard title for a software engineering role — functionally similar to "Software Engineer" at most other companies, just Amazon’s specific naming convention.
What is the difference between a Data Scientist and an Applied Scientist?+
At companies like Amazon, "Applied Scientist" often implies a stronger research and machine-learning-model-building focus, sometimes expecting an advanced degree, while "Data Scientist" more often covers a broader mix of analysis, modeling, and business-facing work — but exact usage varies by company, so always check the specific role’s actual responsibilities.
What is the difference between a Data Engineer and a Data Analyst?+
A Data Engineer builds and maintains the pipelines and infrastructure that move and store data; a Data Analyst works with data that is already accessible to answer specific business questions — different skill sets (engineering vs. analysis) even though both work closely with data.
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