Data QA Developer with Cypress Salary in 2024
How statistics are calculated
We count how many offers each candidate received and for what salary. For example, if a Data QA developer with Cypress with a salary of $4,500 received 10 offers, then we would count him 10 times. If there were no offers, then he would not get into the statistics either.
The graph column is the total number of offers. This is not the number of vacancies, but an indicator of the level of demand. The more offers there are, the more companies try to hire such a specialist. 5k+ includes candidates with salaries >= $5,000 and < $5,500.
Median Salary Expectation – the weighted average of the market offer in the selected specialization, that is, the most frequent job offers for the selected specialization received by candidates. We do not count accepted or rejected offers.
Trending Data QA tech & tools in 2024
Data QA
What is Data Quality
A data quality analyst maintains an organisation’s data so that they can have confidence in the accuracy, completeness, consistency, trustworthiness, and availability of their data. DQA teams are in charge of conducting audits, defining the data quality standards, spotting outliers, and fixing the flaws, and play a key role at all stages in the data lifecycle. Without DQA work, strategic plans will fail, operations will go awry, customers will leave, and organisations will face substantial financial losses, as well as a lack of customer trust and potential legal repercussions due to poor-quality data.
This is a job that has changed as much as the hidden infrastructure that transforms data into insight and then powers the apps that we all use. I mean, it’s changed a lot.
Data Correctness/Validation
This is the largest stream of all the tasks. When we talk about data correctness, we should be asking: what does correctness mean to you, for this dataset? Because it would be different for every dataset and every organisation. The commonsense interpretation is that it must be what your end user (or business) wants from the dataset. Or what would be an expected result of the dataset.
We can obtain this just by asking questions, or else reading through the list of requirements. Here are some of the tests we might run, in this stream:
Finding Duplicates — nobody wants this in their data.
– Your data contains unique/distinct values in that column/field. Will the returned value be a unique/distinct value in that column/field?
– Any value that can be found in your data is returned.
Data with KPIs – If data has any columns we can sum, min or max on it’s called a key performance indicator. So basically any models which are mostly numeric/int column. eg: Budget, Revenue, Sales etc. If there is data comparison between two datasets then below tests applies:
– Comparing counts between two datasets — get the difference in count
– Compare the unique/distinct values and counts for columns – find out which values are not present in either of the datasets.
– Compare the KPIs between two datasets and get the percentage difference between them.
– Replace missing values – missing in any one of the datasets with primary or composite primary key. This can be done in a data source that does not have primary key too.
– Perform the metrics by segment for the individual column value — that can help you determine what might be going wrong if the count of values in the Zoopla-side doesn’t match the count on the Rightmove-side or if some of the values are missing.
Data Freshness
This is an easy set. How do we know if the data is fresh?
An obvious indication here is to check if your dataset has a date column, in which case, you just check the max date. Another one is, when the data was pulled into a particular table, all of this can be converted into a very simple automated checks, which we might talk about in a later blog entry.
Data Completeness
This could be an intermediate step in addition to data correctness, but how do we know to get there if the space of answers is complete?
To do this test, check if any column has all values null in it perhaps that’s okay, but most of the time it’s bad news.
Another test would be one-valuedness: whether everywhere on the column all values are the same, probably in some cases that would be a fine result, but probably in other cases that would be something we’d rather look into.
What are Data Quality Tools and How are They Used?
Data quality tools are used to improve, or sometimes automate, many processes required to ensure that data stays fit for analytics, data science, and machine learning. For example, such tools enable teams to evaluate their existing data pipelines, identify bottlenecks in quality, and even automate many remediation steps. Examples of activities relating to guaranteeing data quality include data profiling, data lineage, and data cleansing. Data cleansing, data profiling, measurement, and visualization tools can be used by teams to ‘understand the shape and values of the data assets that have been acquired – and how they are being collected’. These tools will call outliers and mixed formats. In the data analytics pipeline, data profiling acts as a quality control gate. And each of these are data management chores.
Where is Cypress used?
End-to-End Testing Extravaganza
- Frontend devs cheer as Cypress automates browser clickety-clacks, checking if sites play nice like good digital citizens.
Continuous Integration Party
- Git hooks and CI systems invite Cypress for continuous test shindigs, ensuring code dances smoothly after each commit.
Debugging Time Machine
- Turn back the clock! Cypress's snapshots and videos are like your code’s own 'remember when' moments for squashing bugs.
Component Health Check-Ups
- Cypress gives React components their regular health check, making sure they're fit to be rendered without causing a virtual DOM-ache.
Cypress Alternatives
Selenium
Automated testing framework for web applications. Cross-browser support with integration for various languages.
from selenium import webdriver
driver = webdriver.Chrome()
driver.get("http://www.example.com")
element = driver.find_element_by_id("element_id")
element.click()
- Widely used and mature.
- Cross-browser and cross-platform.
- Supports multiple programming languages.
- Can be complex to set up.
- Slower execution compared to some modern tools.
- Occasional flakiness due to timing issues.
Playwright
Node library to automate the Chromium, Firefox, and WebKit with a single API.
const playwright = require('playwright');
(async () => {
const browser = await playwright.chromium.launch();
const page = await browser.newPage();
await page.goto('http://www.example.com');
await page.click('#element_id');
await browser.close();
})();
- Supports multiple browsers with one API.
- Fast execution and reliable.
- Handles modern web features well.
- Node.js ecosystem may not suit all devs.
- Relatively new with smaller community.
- Lacks some integrations present in older frameworks.
TestCafe
End-to-end testing framework that runs tests in multiple browsers at once, without plugins.
import { Selector } from 'testcafe';
fixture `Getting Started`
.page `http://www.example.com`;
test('My first test', async t => {
await t
.click('#element_id')
.expect(Selector('#element_id').innerText).eql('Expected Text');
});
- Requires no WebDriver, straightforward setup.
- Concurrent test execution across browsers.
- Useful for non-developers due to simplicity.
- Focus on front-end may miss backend issues.
- Lesser community support compared to Selenium.
- Debugging can be more complex.
Quick Facts about Cypress
The Dawning of the Cypress Era
What if I told you that in 2015, an open-source test automatron grew roots in the software realm? That's right, the ingenious Brian Mann decided that battling with flaky tests should be thrown into the annals of history, hence Cypress was born! This wondrous tool said au revoir to Selenium's traditional complexities and threw a welcome party for straightforward, JavaScript-loving e2e testing.
The Almighty Time Travel Trick
Imagine clicking your heels, whispering "there's no place like the home button", and actually rewinding time in your tests! In the land of Cypress, that's less of a fairytale and more of a daily routine. Since inception, it armed developers with the power to travel through time... well, sort of. Its ability to snapshot at every command enables testers to scroll through time, inspecting each step like a meticulous detective amidst a sea of code.
cy.clock()
cy.visit('/page')
cy.tick(1000) // Leap forward in time by 1 second
The Cypress 10-Mark Celebration
Hold onto your keyboards, folks, for in 2021 Cypress v10 descended upon us with an absolute bang! Not only did it continue to revolutionize the way tests prance and dance through browsers, but it also donned a strikingly new interface. This tech glow-up brought component testing into the spotlight, making it a one-stop shop extravaganza. It was like the software declared, "Why choose either/or when you can have it all?"
What is the difference between Junior, Middle, Senior and Expert Cypress developer?
| Seniority Name | Years of Experience | Average Salary (USD/year) | Responsibilities & Activities | Quality-Wise |
|---|---|---|---|---|
| Junior Developer | 0-2 | 40,000-70,000 |
| Limited to foundational practices |
| Middle Developer | 2-4 | 70,000-100,000 |
| Consistent, with keen attention to detail |
| Senior Developer | 4-6 | 100,000-130,000 |
| High-quality outputs, drives testing excellence |
| Expert/Team Lead | 7+ | 130,000-160,000+ |
| Exceptional quality, innovation-led approach |
Top 10 Cypress Related Tech
JavaScript: The Lingua Franca of Web Testing
JavaScript is like the bread and butter of Cypress; without it, you're just pressing Ctrl+C and Ctrl+V without knowing why. As a dynamically typed language, it's super forgiving – like that one friend who doesn't mind if you're late. You absolutely need to know your way around JavaScript to whisper sweet nothings into Cypress's ear. Arrays, objects, closures – get cozy with them, they're your new bffs.
Cypress Framework: Your Test Automation Sidekick
If JavaScript is your trusted steed, then Cypress is your shining armor in the battleground of test automation. With its fluent API that gels with Mocha and Chai, you can write end-to-end tests so elegantly, they look like Shakespeare wrote them – if Shakespeare was into coding, which he totally should have been. It's not just a tool; it's a whole test automation philosophy, a creed, the "one tool to rule them all" in the realm of web testing.
cy.visit('https://www.example.com');
cy.contains('Save the Galaxy').click();
HTML/CSS: The Beautifiers
Ah, HTML and CSS, the dynamic duo that makes the web look less like a wall of green Matrix code. Even though Cypress is there to test, not to make things pretty, if you can't distinguish a class from an id, trouble's brewing. Imagine trying to explain to Cypress which button to press, but you're both looking at an abstract painting of Picasso – that's debugging without HTML/CSS knowledge.
Node.js: The JavaScript Overlord
Node.js is the Gandalf of JavaScript runtime environments: venerable, wise, and powerful. It empowers Cypress to perform its magic and orchestrate those nasty async operations without breaking a sweat. Node.js and NPM (Node Package Manager) are as crucial for Cypress as coffee is for developers; it’ll handle packages, plugins, and keep everything running smoother than a vinyl record.
Git: The Time-Traveling Code Wizard
Working without Git is like tightrope walking without a safety net – exhilarating but you might faceplant spectacularly. Version control is the spine of collaborative coding, and Git is the chiropractor. Master the arcane arts of branching, merging, and committing, so when you do something catastrophic, you can just whisper "Git me outta here!" and reset the space-time continuum of your code.
CI/CD Tools: The Assembly Line of Code
If you want your Cypress tests to be part of the cool automated deployment kids club, you gotta be tight with continuous integration and delivery tools (CircleCI, Jenkins, or GitHub Actions, to throw some names). They're your ticket to an elite coding dojo where code is tested, built, and deployed without you lifting a finger. It’s like a talent show for your code, and CI/CD is the stage.
API Testing: The Detective Work
APIs are the secret whispers between services, and with Cypress, you’re the omnipotent eavesdropper. API testing is crucial; imagine you're a detective deciphering whispers for clues where each HTTP status is a twist in the plot. Get good at making sense of the '200 OKs' and '400 Bad Requests'; those are the bread crumbs leading you through the dark forest of back-end services.
Testing Libraries (Mocha/Chai): The Spices to Your Testing Dish
You know how food tastes bland without spices? That's plain testing without Mocha and Chai. These libraries are like salt and pepper sprinkled over your test cases making assertions readable, and you understand what went wrong without pulling your hair out. Expectations and should syntax will become your allies as you test the living zeroes and ones out of your applications.
expect(tea).to.have.property('flavors')
.with.length(3);
Browser Developer Tools: The Cyberspace Sherlock Holmes Kit
Browser DevTools are your magnifying glass, your forensic lab in the world of web development. These tools are like a Swiss Army knife; from DOM inspection to sifting through network requests, there's a tool for every mystery. Master these, and you'll debug with the elegance and precision of Sherlock, minus the deerstalker hat, but feel free to wear one if it helps.
Visual Testing Tools: The Art Critics of UI
Think of visual testing tools as that picky art critic examining your website’s aesthetics. Cypress can integrate with tools like Percy or Applitools to make sure your CSS didn't go rogue and your website’s layout isn’t throwing a tantrum on different screen sizes. It's like having a meticulous art restorer scrutinizing every pixel to make sure everything is picture-perfect.