Understand tech roles and career ladders, pick a realistic learning route, build portfolio evidence, and navigate postings, interviews and your first 90 days.

Foundations for Software, Data, Design & Tech Education Careers

## Why it matters

"Working in tech" covers very different jobs. A data analyst spends the day in SQL and dashboards; a cybersecurity engineer reviews alerts and hardens systems; a UI/UX designer interviews users and builds prototypes; a computer science teacher plans lessons and grades code. Picking a target role early lets you choose the right courses, build the right portfolio and read job postings with confidence. Picking the wrong one, or no target at all, is one of the most common reasons learners drift for months.

## The core idea: what you produce

A useful way to compare roles is to ask **what you produce** at the end of a typical week and **who uses it**.

## Software and interfaces

| Role | A typical week | Main outputs | Core tools |
|---|---|---|---|
| **Software developer** | turn tickets into working, tested code; review teammates' pull requests; fix bugs | features, tests, code reviews | a language (JavaScript, Python, Java, C#...), Git, an IDE, a database |
| **UI developer** | build the screens users touch, match designs, make them accessible and responsive | components, pages, style systems | HTML, CSS, JavaScript, React, browser dev tools |
| **Mobile developer** | build and release iOS/Android apps; handle app-store reviews and device quirks | app releases | Swift/Kotlin or React Native/Flutter, Xcode, Android Studio |
| **Video game designer** | design mechanics, levels and systems; prototype and playtest; write design docs | prototypes, design documents, tuned gameplay | a game engine (Unity, Unreal, Godot), spreadsheets, scripting |

## Data

| Role | A typical week | Main outputs | Core tools |
|---|---|---|---|
| **Data analyst** | answer business questions from data; clean data; build reports | dashboards, analyses, recommendations | SQL, spreadsheets, Python or R, a BI tool |
| **Data scientist** | build statistical and predictive models; design experiments | models, experiment results, analyses | Python/R, statistics, SQL, notebooks |
| **Machine learning engineer** | put models into production; build data and training pipelines; monitor models | deployed models, ML services | Python, ML frameworks, cloud, containers |

## Infrastructure and security

| Role | A typical week | Main outputs | Core tools |
|---|---|---|---|
| **Cybersecurity engineer** | monitor alerts, investigate incidents, harden systems, review designs for risk | detections, fixes, security reviews | Linux, networking, SIEM tools, scripting |
| **Cloud engineer** | build and run cloud infrastructure, automate deployments, manage cost | infrastructure as code, pipelines | AWS/Azure/GCP, Linux, Terraform, CI/CD |
| **Database administrator** | keep databases fast, backed up, secure and available; often on call | backups, tuned queries, upgrades | SQL, a database engine (PostgreSQL, SQL Server, Oracle), Linux |
| **Systems analyst** | gather requirements from the business and translate them into system changes | requirements, process maps, test plans | SQL, diagrams, ticketing tools, interviews |

## Design, delivery and teaching

| Role | A typical week | Main outputs | Core tools |
|---|---|---|---|
| **UI/UX designer** | research user needs, sketch, prototype, test with users, hand off to developers | research findings, wireframes, prototypes | Figma, research methods, design systems |
| **IT project manager** | plan scope, schedule and budget; run meetings; manage risks and stakeholders | plans, status reports, decisions | project tools, spreadsheets, Agile methods |
| **Technical trainer** | design and deliver training on a product or technology; measure learning | courses, labs, workshops | slides, labs, a learning management system |
| **Computer science teacher** | plan and teach classes, grade work, support students | lessons, assessments | a teaching language (often Python or JavaScript), classroom tools |

## Worked example: same project, different jobs

Picture a company launching a "book a delivery slot" feature in its app:

- The **systems analyst** interviews the operations team and writes the requirements.
- The **UI/UX designer** tests three slot-picker designs with customers.
- **UI**, **software** and **mobile developers** build the screens and the API.
- The **database administrator** checks the new tables and indexes will cope with peak traffic.
- The **cloud engineer** sets up the infrastructure and deployment pipeline; the **cybersecurity engineer** reviews it for risks.
- The **IT project manager** keeps the work on schedule.
- After launch, the **data analyst** measures how many customers use slots, and the **data scientist** forecasts demand so the company knows how many drivers to schedule. A **machine learning engineer** puts that forecast model into production.
- The **technical trainer** teaches the support team the new feature.

Each role sees the same project from a different angle. Notice which part you would most enjoy doing every week.

## How to research a role properly

- Read the **O*NET** profile (https://www.onetonline.org) for tasks, skills and typical education, and the US **Bureau of Labor Statistics Occupational Outlook Handbook** (https://www.bls.gov/ooh/) for pay and outlook. (Checked on 2026-10-23.)
- Read 10 real job postings for the role in your area (lesson 7 shows how).
- Talk to one or two people who do the job. Ask what they did last Tuesday, not what the job is "like".

## Common mistakes

- **Choosing by job title or salary alone.** The daily work matters more for whether you will last.
- **Assuming all tech jobs are coding jobs.** Analysts, designers, project managers and trainers code little or not at all.
- **Targeting five roles at once.** Pick one target and one backup that share skills.
- **Relying on social media "day in the life" videos.** They show the highlights, not the meetings and debugging.

## Quick recap

- Compare roles by what they produce and who uses it.
- Software and UI roles build products; data roles turn data into decisions; infrastructure and security roles keep systems running safely; design, project and teaching roles shape, deliver and explain the work.
- Research with O*NET, the BLS handbook, real postings and real people.
- Choose one target role and one backup.


Compare the day-to-day work, tools and outputs of the main software, data, security, design and tech education roles.

Roles in software, data, security, and design

Every IT Job Explained in 10 Minutes (Helpdesk to Cloud Architect)

UX Design Careers | Google UX Design Certificate

## Why it matters

This platform takes you from beginner to the point where you can do mid-level work. It helps to know what that means. Job titles vary (Developer I/II, Associate/Analyst, Engineer 1/2), but most companies use a **career ladder**: a written list of what is expected at each level. Knowing the ladder helps you write a stronger CV, answer interview questions at the right level, and see what to practise next.

## The core idea: scope and independence

The difference between junior and mid-level is rarely "knows more syntax". It is mostly about **scope** (how big a piece of work you own) and **independence** (how much help you need to finish it well).

| | Junior (entry level) | Mid-level |
|---|---|---|
| **Scope** | well-defined tasks: one bug, one screen, one report | whole features or projects that take weeks |
| **Independence** | needs guidance on approach; work is reviewed closely | chooses an approach, asks for help at the right moments |
| **Quality** | code or work that works; reviewers catch issues | anticipates edge cases, writes tests, documents decisions |
| **Communication** | updates their lead | updates the team and stakeholders; explains trade-offs |
| **Ambiguity** | clarifies requirements with help | turns a vague request into a plan |
| **Helping others** | learns from reviews | reviews others' work and helps juniors |

Most people spend roughly two to four years at the junior level, but it depends far more on the breadth of what you have done than on time served.

## What it looks like in different roles

**Software or UI developer.** A junior fixes a bug in an existing form when given the ticket. A mid-level developer takes "customers want to save their basket" and designs the data model, the API and the UI, splits it into pull requests, writes tests, and flags that the change affects the checkout team.

**Data analyst.** A junior writes the query the manager specified. A mid-level analyst is asked "why did sign-ups drop?", decides which data to look at, checks data quality, considers seasonality, and presents a recommendation with its limitations.

**Cybersecurity engineer.** A junior triages alerts using a playbook. A mid-level engineer investigates an unusual incident without a playbook, writes a new detection rule, and improves the playbook for next time.

**UI/UX designer.** A junior produces screens for a defined flow. A mid-level designer plans and runs the research, defends design decisions with evidence, and works with developers on trade-offs.

**IT project manager or systems analyst.** A junior tracks tasks and takes notes. A mid-level PM or analyst owns a project's plan, spots risks early and negotiates scope with stakeholders.

**Technical trainer or CS teacher.** A new trainer delivers an existing course. An experienced one designs a course from a needs analysis and changes it based on learner results.

## Worked example: one ticket, two levels

Ticket: "The monthly report is slow."

- **Junior response:** "I added an index on `orders.created_at` and the query now runs in 3 seconds instead of 40. PR is ready for review."
- **Mid-level response:** "The report was slow because it scans every order. I added an index on `orders.created_at` (40 s to 3 s) and measured the effect on insert speed (no visible change). The same pattern affects two other reports, so I opened tickets for them. I also suggested to the finance lead that we schedule the report overnight, since they only read it in the morning."

Both fixed the problem. The mid-level answer **measured** the result, checked **side effects**, looked for **related problems** and thought about the **user's real need**.

## How to grow faster

- **Ask for the "why"** behind every task, not just the "what".
- **Finish things.** Small projects shipped beat big ones abandoned.
- **Write things down:** decisions, how you tested, what you learned.
- **Read code reviews and feedback as a curriculum.** The same comment twice is a pattern to fix.
- **Keep a "brag document"**: a running list of what you did and its impact. It makes reviews, promotions and CV updates much easier.

## Common mistakes

- **Equating seniority with years.** Five years repeating the same task is not mid-level experience.
- **Never asking for help** (wastes days) or **always asking** (never builds independence). Try for a set time, then ask with what you tried.
- **Focusing only on technical skill.** Communication and judgement are a large part of every ladder.
- **Applying only to jobs that match your current level exactly.** Postings often list more than they need; lesson 7 covers this.

## Quick recap

- Career ladders describe expectations at each level.
- Junior to mid-level is mostly about scope, independence, quality and communication.
- Mid-level work measures results, checks side effects and considers the user's real need.
- Grow by asking why, finishing work, writing things down and tracking your impact.


Describe the skills, scope and independence that separate junior from mid-level tech professionals.

Junior to mid-level: what changes

Senior Developers vs. Junior Developers, What's The Difference?

Write down your target role and one backup role from lesson 1.

Find your target role in the "What each career really requires" table in this lesson and copy its requirements. Mark each one as required, common or optional.

Open the official source for one listed requirement (a certification body, O*NET or your state's teacher licensing page) and note one fact that is different from what you expected. Write the date you checked.

Write down your constraints honestly: hours per week you can study, money you can spend, whether you can stop working, and your deadline.

Pick a primary route (degree, bootcamp, certification-led or self-taught) and write two sentences on why it fits your constraints and your target role.

If you are considering a paid program, write down three questions to ask it: audited job outcomes, total cost including fees, and refund policy. Do not sign anything today.

Write a plan for the next 12 weeks: the courses on this platform you will finish, one piece of portfolio evidence, and one person in the role you will talk to.

## Why it matters

People get into tech through many routes, and each has real costs and real limits. Some roles genuinely require a credential (teaching in a US public school needs a state licence; some government security jobs need a clearance). Others are open to anyone who can show strong evidence. Choosing a route that matches both your target role and your life (money, time, family, deadlines) matters more than choosing the "best" route in general.

## The four main routes

| Route | Strengths | Limits | Best when |
|---|---|---|---|
| **Degree** (associate, bachelor's, master's) | broad foundations, internships, recruiter pipelines, required for some roles and many visas | years of time, high cost in many countries | your target role or employer requires it; you are early in your career; you want research or ML roles |
| **Bootcamp** (weeks to months) | structure, pace, a cohort, career services | cost; quality and outcomes vary widely; little depth in fundamentals | you need structure and can study full time; you have checked audited outcomes |
| **Certification-led** | clear syllabus; valued in IT, cloud, security and project management | a certificate alone rarely gets a job without hands-on evidence | your target is cloud, security, IT support, project management or training |
| **Self-taught** (free courses like this one, books, projects) | free or cheap, flexible, builds self-direction | no external structure or credential; easy to drift | you are disciplined, have a clear plan and will build public evidence |

Most successful people **combine** routes: a degree plus projects, or self-teaching plus a certification plus open source.

## What each career really requires

These are honest summaries of what employers expect beyond this platform. They change over time, so check the official sources.

| Career | Beyond the platform |
|---|---|
| Data analyst | Portfolio first; a bachelor's (statistics, economics, CS, business) is common; optional Google Data Analytics or Microsoft PL-300 certificates. |
| Data scientist | Bachelor's in a quantitative field, master's common; portfolio and internships matter more than certificates. |
| Machine learning engineer | BS/MS in CS or similar plus production software experience; cloud ML certifications optional. |
| Software developer | BS in CS common but not required; portfolio, internships and open source carry most weight. |
| UI developer | Portfolio over degree; optional IAAP CPACC accessibility certification. |
| Mobile developer | Shipped apps in the stores (developer accounts have fees); BS in CS optional. |
| Video game designer | Portfolio of prototypes and game-jam games; game design or CS degree common; no licence. |
| UI/UX designer | Portfolio with case studies; optional NN/g UX certification; no licence. |
| Cybersecurity engineer | CompTIA Security+ then CySA+; CISSP needs 5 years' experience; some roles need a degree or security clearance. |
| Systems analyst | Bachelor's in IS, CS or business typical; IIBA ECBA, then CCBA/CBAP with experience. |
| Database administrator | Bachelor's in IT/CS common; vendor certifications (such as Microsoft DP-300, Oracle) plus on-call experience. |
| Cloud engineer | AWS, Azure or Google Cloud associate certifications plus hands-on Linux and networking experience; bachelor's often preferred. |
| IT project manager | CAPM early; PMP needs about 36 months leading projects; PSM/CSM optional; bachelor's typical. |
| Technical trainer | Deep expertise in the subject taught; optional ATD or vendor trainer programs (such as CompTIA CTT+ or Microsoft Certified Trainer). |
| Computer science teacher | **Required:** college teaching usually needs a master's or PhD; K-12 public schools need a bachelor's plus a state teaching licence or CS endorsement. |

Official sources (Checked on 2026-10-23.): CompTIA https://www.comptia.org/certifications · ISC2 CISSP https://www.isc2.org/certifications/cissp · IIBA https://www.iiba.org · PMI https://www.pmi.org/certifications · IAAP https://www.accessibilityassociation.org · NN/g https://www.nngroup.com/ux-certification/ · AWS https://aws.amazon.com/certification/ · Microsoft https://learn.microsoft.com/credentials/ · ATD https://www.td.org · O*NET https://www.onetonline.org. For K-12 teaching, use your state education department's licensing page. Fees, exam content and experience rules change, so read the current page rather than relying on a summary.

## Worked example: two learners, two routes

**Maya, 19, wants to be a data scientist.** Data science postings near her mostly ask for a quantitative bachelor's degree, and many ask for a master's. She chooses a statistics degree, uses this platform for Python and SQL alongside it, and targets a summer internship in year two. Self-teaching alone would make her target role much harder to reach.

**Sam, 34, works full time and wants to be a cloud engineer.** He has eight hours a week and cannot stop working. He follows the platform's Linux, networking and cloud courses, studies for an associate-level cloud certification, and builds two small infrastructure projects on a free tier, documenting them publicly. He looks for an internal move into IT operations first, because the jump from an unrelated job straight to cloud engineer is rare.

Different routes, both realistic.

## Checking a paid program

If you consider a bootcamp or paid course, ask for:

- **Audited outcomes**: what share of graduates were working in the field within six months, and how "working in the field" was defined.
- **Total cost**, including financing, and the refund policy.
- **Who teaches** and how much one-to-one help you get.

Be wary of guaranteed-job claims and pressure to sign quickly.

## Common mistakes

- **Buying a credential the role does not need**, or skipping one it requires.
- **Collecting certificates without building anything.** Employers hire evidence.
- **Planning for an unrealistic pace.** Ten hours a week, sustained, beats forty hours for two weeks.
- **Expecting a quick switch.** Entry-level tech hiring is competitive; plan for months, not weeks.

## Quick recap

- Degrees, bootcamps, certifications and self-teaching each fit different goals and lives; most people combine them.
- Some careers have real gates (teaching licences, experience rules for CISSP and PMP); check official sources.
- Choose a route from your target role's requirements and your constraints.

## Try it

Open the **Do** tab to choose your route and write a 12-week plan.


Weigh degrees, bootcamps, certifications and self-teaching against your target role's real requirements and your situation.

Degrees, bootcamps, certifications, self-taught

How to Become a Developer

Compare the day-to-day work of software, data, security, design and tech education roles, see what changes from junior to mid-level, and choose a realistic learning route.