Data Quality Analyst

Data Platform

Job Family

AU$80k

Salary

Average salary in Australia

10%

Job Growth

The number of positions relative to last year

Open Roles

Job openings on Alooba Jobs

Data Quality Analysts play a crucial role in maintaining the integrity of data within an organization. They are responsible for identifying, correcting, and preventing inaccuracies in data sets. This role involves using analytical tools and methodologies to monitor and maintain the quality of data. Data Quality Analysts collaborate with other teams to ensure that data is accurate, reliable, and suitable for business decision-making. They typically use SQL for data manipulation, employ data quality tools, and leverage BI tools like Tableau or PowerBI for reporting and visualization.

Typical Responsibilities & Duties

Perform data quality assessments and audits to ensure data accuracy and integrity
Identify and resolve data quality issues through root cause analysis and corrective actions
Collaborate with IT and business stakeholders to define data quality standards and rules
Develop and maintain data cleansing routines to enhance data quality
Monitor data quality metrics and report on data quality to stakeholders
Provide support and guidance on best practices for data management and quality
Develop data quality dashboards and reports for ongoing monitoring and analysis
Participate in data governance initiatives to ensure adherence to data quality standards
Work with cross-functional teams to implement data quality improvements
Assist in the development of policies and procedures for data quality management
Analyze large datasets to identify patterns and trends impacting data quality

Typical Required Skills & Experiences

Proven experience in data quality analysis, management, or a related field
Proficiency in SQL and experience with data analysis tools such as Python or R
Familiarity with data quality tools and methodologies
Strong analytical and problem-solving skills
Experience with BI tools like Tableau or PowerBI for reporting and visualization
Excellent communication skills and ability to work collaboratively across teams
Understanding of data governance and data management best practices
Bachelor's degree in Information Technology, Computer Science, Data Science, or a related field
Attention to detail and commitment to data accuracy and integrity
Ability to multitask and manage multiple projects simultaneously

Core Data Quality Analyst Required Skills

Accessibility

Ad Quality Score Agile

Business Intelligence Development

Customer Data Platforms Data

Data Quality Assurance

Data Stewardship

Data Storage Framework

Data-Driven Decision Making

Database & Storage Systems

Database Management Tool

Distributed Event Store

Econometric Modeling

Encryption Entropy

Entropy

Factual Accuracy Finance

Finance

Foreach Loops

Functional Requirements

Missing Value Treatment

Object-Oriented Programming

Orderliness

Project Management

Quality Assurance Qubole

Qubole

Regular Expressions Sales

Sales

Sales Analytics SAS

SAS

Seaborn

Secure Programming

Segmentation

Single Responsibility Principle Splunk

Tracking Codes UAT

UAT

While Loop

Discover how Alooba can help identify the best Data Quality Analysts for your team

Data Quality Analyst Levels

Intern Data Quality Analyst

An Intern Data Quality Analyst is a budding professional who ensures the accuracy and consistency of data. They are responsible for monitoring and maintaining the quality of data that an organization uses for decision-making. Their role is crucial in preventing data errors and inaccuracies that could impact business insights and operations.

Graduate Data Quality Analyst

A Graduate Data Quality Analyst is a detail-oriented professional who ensures the accuracy and consistency of data. They are responsible for data validation, data cleansing, and improving data quality processes. Their work is vital in maintaining the integrity of data, which underpins sound, data-driven decision-making.

Junior Data Quality Analyst

A Junior Data Quality Analyst is an essential role in maintaining the accuracy and integrity of data within an organization. They assist in identifying, correcting, and preventing data quality issues, ensuring the reliability of data for decision-making and operations.

Data Quality Analyst (Mid-Level)

A Data Quality Analyst is a detail-oriented professional who ensures the accuracy and consistency of data. They identify, clean, and safeguard data, ensuring it is reliable for analysis and decision-making. Their expertise in data governance, quality assurance, and problem-solving makes them vital to data-driven organizations.

Senior Data Quality Analyst

A Senior Data Quality Analyst is an experienced professional who ensures the accuracy, consistency, and reliability of data. They design and implement data quality management strategies, monitor data quality metrics, and lead data quality improvement initiatives. Their work is crucial for maintaining the integrity of data and supporting data-driven decision-making.

Lead Data Quality Analyst

A Lead Data Quality Analyst is a seasoned professional who ensures the accuracy, consistency, and reliability of an organization's data. They implement data quality standards, manage data quality projects, and lead teams in maintaining the integrity of data assets. Their role is critical in ensuring data-driven decisions are based on accurate and trustworthy data.

Over 50,000 Candidates Can't Be Wrong

A great experience overall, smooth platform, easy to use, challenging questions and very relevant to the role.

Yoel

Senior marketing analyst for travel multinational

This is really different kind of experience through a interview process, where I like the journey and the motive of this screening process.

Srishti

Strategy analyst candidate for large internet company

Overall, I found the test to be well-designed and comprehensive, effectively assessing the relevant skills and knowledge required for the position. The questions were thought-provoking and challenged me to think critically.

Sami

Senior marketing manager candidate for leading SE Asia corporate

Overall, I found the test platform to be very user-friendly and well-designed. It provided a smooth and efficient experience throughout the assessment.

Rahul

Marketing candidate at global travel enterprise

Our Customers Say

I was at WooliesX (Woolworths) and we used Alooba and it was a highly positive experience. We had a large number of candidates. At WooliesX, previously we were quite dependent on the designed test from the team leads. That was quite a manual process. We realised it would take too much time from us. The time saving is great. Even spending 15 minutes per candidate with a manual test would be huge - hours per week, but with Alooba we just see the numbers immediately.

Shen Liu, Logickube (Principal at Logickube)

I wouldn't dream of hiring somebody in a technical role without doing that technical assessment because the number of times where I've had candidates either on paper on the CV, say, I'm a SQL expert or in an interview, saying, I'm brilliant at Excel, I'm brilliant at this. And you actually put them in front of a computer, say, do this task. And some people really struggle. So you have to have that technical assessment.

Mike Yates, The British Psychological Society (Head of Data & Analytics)

We get a high flow of applicants, which leads to potentially longer lead times, causing delays in the pipelines which can lead to missing out on good candidates. Alooba supports both speed and quality. The speed to return to candidates gives us a competitive advantage. Alooba provides a higher level of confidence in the people coming through the pipeline with less time spent interviewing unqualified candidates.

Scott Crowe, Canva (Lead Recruiter - Data)

How can you accurately assess somebody's technical skills, like the same way across the board, right? We had devised a Tableau-based assessment. So it wasn't like a past/fail. It was kind of like, hey, what do they send us? Did they understand the data or the values that they're showing accurate? Where we'd say, hey, here's the credentials to access the data set. And it just wasn't really a scalable way to assess technical - just administering it, all of it was manual, but the whole process sucked!

Cole Brickley, Avicado (Director Data Science & Business Intelligence)