Data QA Developer with JMeter Salary in 2024

Total:

Median Salary Expectations:

$4,752

Proposals:

How statistics are calculated

We count how many offers each candidate received and for what salary. For example, if a Data QA developer with JMeter 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 JMeter used?

Load Test Your Web Dreams

Imagine web servers sweating under pressure? JMeter is your gym coach for websites, making sure they can lift heavy traffic without crashing the browser party.

API Muscle Challenge

APIs need to flex their muscles too! JMeter throws API requests like dodgeballs to see if they dodge, catch, or just flop on the digital court.

Performance Potion Brewing

Concocting a wicked brew of speedy responses? JMeter is the wizard mixing the potion, ensuring your application spells enchant snappy spells under the hood.

Database Gymnastics

Your database better be ready for gymnastics, twisting through queries at lightning speed. JMeter judges the database floor routine, scoring the flips and flops of data retrieval.

JMeter Alternatives

LoadRunner

LoadRunner by Micro Focus is a widely-used performance testing tool for predicting system behavior and performance. It enables the creation of realistic load scenarios.


    // Example LoadRunner Vuser script
    Action()
    {
        web_url("Home",
            "URL=http://www.example.com",
            "TargetFrame=",
            "Resource=0",
            "RecContentType=text/html",
            "Referer=",
            "Snapshot=t1.inf",
            "Mode=HTML",
            LAST);
  
        return 0;
    }

Supports a wide range of applications.

Advanced analysis and reporting capabilities.

Requires higher investment and expertise.

Gatling

Gatling is an open-source load and performance testing framework based on Scala, Akka, and Netty with a focus on web applications. It offers a DSL for test scripting.


    // Basic Gatling scenario script
    val scn = scenario("MyScenario")
        .exec(http("Request")
        .get("/"))
    
    setUp(scn.inject(atOnceUsers(10)).protocols(http.baseUrl("https://example.com")))

Provides an expressive DSL for scripting.

Open-source and extensible.

Requires familiarity with Scala.

Apache Bench (ab)

Apache Bench is a simple, command-line tool for benchmarking and load testing web servers, often used to get a quick assessment of server performance.


    // Running a simple Apache Bench test
    ab -n 100 -c 10 http://www.example.com/

Simple to use for basic testing needs.

Minimal setup required.

Limited functionality and reporting.

Quick Facts about JMeter

JMeter Crashes the Performance Party - 1998

Picture it: 1998, the aroma of Fresh Prince still lingers in the air, and bam! Apache JMeter struts onto the scene, crafted by Stefano Mazzocchi of the Apache Software Foundation. This nifty tool was concocted for the thrill of crushing load test problems - basically the party animal of performance testing!

Unleash the Scripts - The JMeter Revolution!

Fast forward, and JMeter pulls a rabbit out of its hat: it's no one-trick pony! This bad boy dances with Java to test performance like a boss, but get this—it's a script kiddie's paradise. With support for scripting languages like Groovy, you can whip up test scripts like you're a wizard at Hogwarts, minus the wand.

Meet JMeter's Cool Sibling - 5.4.1 Edition

And then along came JMeter 5.4.1, striding in like it owned the place in February 2021. Decked out with glitzy features like a JSON Path extractor and a shiny HTML reporting dashboard, it's like the Tesla of performance testing – high-tech, fancy, and everyone wants a ride!

Example code snippet of a basic JMeter test plan (just kidding, we’re keeping it high-level).

What is the difference between Junior, Middle, Senior and Expert JMeter developer?

Seniority Name	Years of Experience	Average Salary (USD/year)	Responsibilities & Activities
Junior	0-2	50,000 - 70,000	Executing basic JMeter scripts under supervision Assisting in test environment setup Documenting test results Learning best practices from senior team members
Middle	2-5	70,000 - 90,000	Designing and developing moderate complexity JMeter tests Identifying and reporting bugs Maintaining test environments Optimizing test performance
Senior	5-10	90,000 - 120,000	Creating advanced JMeter testing strategies Leading test automation initiatives Mentoring junior colleagues Analyzing and reporting on test results to stakeholders
Expert/Team Lead	10+	120,000 - 150,000+	Directing JMeter testing strategy and framework development Overseeing the testing team and ensuring best practices Collaborating with other department leads Conducting high-level test result analyses and decision-making

Top 10 JMeter Related Tech

Java

Java, this granddaddy of programming languages, isn't just for your grandpa's desktop app! It's the backbone of JMeter, so if you're skimping on your Java skills, you might as well be pouring your coffee down the drain. Brush up on loops, classes, and, of course, the million-and-one ways to handle exceptions without pulling your hair out.
```
      // A simple Java loop example
      for (int i = 0; i < 10; i++) {
          System.out.println("Java is essential for JMeter: " + i);
      }
    
```

Apache Ant

Crucial for JMeter, Apache Ant zips around like a colony of busy little digital insects, automating builds with the finesse of a maestro. You'll want to know your way around its XML build files unless you prefer doing things the hard way... manually, like a caveman etching a wheel for the first time.
```
      
      
        
          
        
      
    
```

Bash Scripting

If JMeter had a Swiss Army knife, Bash would be the little tool you forgot about but absolutely needed at a campsite. A tiny bit of Bash scripting goes a long way, as you'll often automate JMeter tests on servers where clicking isn't a thing. Join the cool kids: script your heart out! #NoMoreManualLabor
```
      #!/bin/bash
      # A simple Bash script to run JMeter tests
      JMeter -n -t my_test_plan.jmx -l test_results.jtl
    
```

Jenkins

Flaunt your JMeter tests with Jenkins in the DevOps fashion show. It's like putting your automated tests on a runway; Jenkins will tirelessly run them, display the trendy test results, and notify the squad if the build breaks down like a model tripping over high heels. Keep it continuous, keep it integrated, stay fabulous.
```
      pipeline {
        agent any
        stages {
          stage('JMeter') {
            steps {
              sh 'JMeter -n -t performance_test.jmx -l results.jtl'
            }
          }
        }
      }
    
```

BlazeMeter

Ever wished JMeter could hit the gym and bulk up? Enter BlazeMeter. It's JMeter on tech-fueled muscle enhancements. Leave the limitations of your local machine behind and let BlazeMeter take your performance testing to the clouds. Just don't forget to brag about your massive user load to your friends!

Git

Git is the time-traveling wizard of source control. Messed up? No problemo, just roll back the changes like they never happened. Collaborating with a team? Presto, you can work on your JMeter scripts in parallel universes and then merge them without casting any dark spells. Accio Git Skills!
```
      # Clone a repository with JMeter scripts
      git clone https://github.com/example/jmeter-tests.git
      
      # Checkout a new branch to work on a new test plan
      git checkout -b feature/new-test-plan
    
```

Docker

Pack your JMeter tests in containers and ship them across the seven seas of server land. Docker is like having a portable testing lab that you can replicate faster than rabbits in spring. Just make sure you understand the dark arts of Docker networks and volumes or things might get overboard!
```
      # Dockerfile snippet to run JMeter in a container
      FROM alpine
      RUN apk add --no-cache jmeter
      CMD ["JMeter", "-n", "-t", "/tests/my_test_plan.jmx", "-l", "/results/results.jtl"]
    
```

Apache Groovy

Fancy adding some extra oomph to your JMeter scripts? Apache Groovy is like your script's personal wizard, casting spells in the form of concise expressions and language-level integration with Java. It's so smooth and dynamic; you'll be weaving test magic with the flick of a wrist.
```
      // Groovy assertion example in a JMeter script
      vars.put("response", prev.getResponseDataAsString())
      if (!prev.isSuccessful()) {
        log.error("Oops! Request failed.")
      }
    
```

Postman

You might think, "Wait, isn't Postman just for RESTful siestas?" Sure, but JMeter and Postman can party together. Design and test your APIs with Postman and then export them to JMeter for that heavy-duty performance testing rave. It's like having a quiet dinner date before hitting the club!

REST Assured

When you've grown weary of JMeter's GUI and yearn to write your performance tests in the tranquility of your IDE, REST Assured is your hermit's retreat. Craft elegant API tests in Java like a barista brewing a delicate espresso. It's just Java, but REST Assured makes it look like poetry.
```
      // REST Assured simple get request
      given().when().get("https://api.example.com/data").then().assertThat().statusCode(200);
    
```