Data Quality Analyst Job Description
Job summary 1
Working closely with the Management team, the Data Quality Analyst will provide quality assurance oversight (data error detection and correction) on business processes where data is collected, stored, transformed, or used. Specifically, you will have the opportunity to assist the team in integrating data assets from a variety of systems and sources (external and internal) into the Company’s systems, ensuring and monitoring the final quality of our internal data stores and flows. Your strong data analysis skills will ensure clean data that can be enacted upon by analytic systems and application code, thereby maintaining our high-quality standards for products and services.
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Job summary 2
The Data Quality Analyst is responsible for developing and delivering data solutions to accomplish technology and business goals. Key responsibilities include data governance tasks associated with the integration, cleaning, transformation, and control of data in operational and analytics data systems. They work with stakeholders, Product Owners, and Software Engineers to aid in the governance of data including contributing to efforts to capture and manage the control inventory, measuring the effectiveness of controls, managing data quality requirements to resolve DQ gaps/issues, and managing all forms of business, technical and operational metadata.
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Job summary 3
The Data Quality Analyst provides research support with a focus on quality assurance, quality control, and process improvement. Functions of еру Data Quality Analyst include protocol subject registration and randomization, clinical research auditing, data and safety monitoring, quality control, participation in general clinical trials education, and committee management. The Data Quality Analysts work closely with investigators, research teams, and biostatisticians to ensure the integrity and quality of clinical trial data. Data Quality Analysts monitor the timely submission and completeness of clinical trial data entry, perform edit checks on the data, issue and resolve data queries, and perform other quality control and data cleanup tasks.
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Job summary 4
The Data Quality Analyst (DQA) will ensure compliance with established data quality procedures while reporting and developing new data quality measures. The DQA will create, document, and maintain business processes and procedures and collaborate with team members to improve workflows and streamline processes. This person should be curious, familiar with data quality methods of analysis, inquisitive about the nuances of the data in our data warehouse, and outspoken in a way that will influence and create change and improvements in both business processes and analytics capabilities.
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Job summary 5
We are looking for dynamic and passionate individuals to join our Data team as Data Quality analysts to help develop and grow our data and insights offering. The team focus is on the complete data quality cycle, from logging and auditing the receipt and processing of data to ensuring data deliverables are of the highest quality. You will be responsible for the execution of data quality routines. This individual will proactively monitor, measure, analyze, execute, track, and report on data quality issues. The Data Quality Analyst will interact with other teams to resolve data quality-related issues.
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Job summary 6
A Data Quality Analyst will monitor the quality of data from organizations to make informed decisions. They examine complex data to optimize the efficiency and quality of the data being collected, resolve data quality problems, and collaborate with database developers to improve systems and database designs. Evaluates, implement, and maintain assigned business systems and applications. Additionally, it serves as a key resource for an assigned customer area to understand and explain business data quality analytics and technical issues and to provide viable analytical solutions.
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Job summary 7
The Data Quality Analyst is responsible for evaluating and ensuring data quality across Company’s various data sources. In addition, the Data Quality Analyst is responsible for planning and executing data tests, evaluation of change over time, and evaluation of new data. This includes studying and evaluating current reporting, utilizing and improving current data evaluation methods, writing test plans/cases, planning the test schedules, coordinating test resources, executing test cases, verifying test results, and maintaining a reusable library of test cases to support future testing.
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Job summary 8
The Data Quality Analyst provides data management and analysis support in the development of company-wide program-specific performance measures. Examines complex data and turns it into information and insights to inform business decisions. Monitors performance and quality control plans to identify issues or ways to improve systems and database designs. Participates in regulatory and quality improvement projects, guiding data collection, analysis, and reporting. Collaborates with cross-functional teams to identify areas where improvements in data quality can be made.
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Job summary 9
We are currently seeking a Data Quality Analyst for a full-time opportunity with an innovative company.
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Job summary 10
The Data Quality Analyst (DQ Analyst) is responsible for ensuring the integrity of data used to support/submit for the various Quality Metrics programs. Responsibilities include remaining current with quality metrics measure specifications, data collection, data analysis, generation of reports, and providing relevant feedback for improved outcomes and better data capture.
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Frequently asked questions
What does a data quality analyst do?
A Data Quality Analyst is responsible for ensuring the accuracy, completeness, consistency, and reliability of data used by an organization. The job duties of a Data Quality Analyst may include:
Data Analysis: Analyzing data to identify issues, anomalies, or errors that may affect data quality.
Data Profiling: Profiling data to understand data structure, data relationships, and data dependencies.
Data Cleansing: Cleaning and standardizing data to ensure consistency and completeness.
Data Validation: Validating data to ensure that it meets defined quality standards, such as accuracy, completeness, and reliability.
Data Monitoring: Monitoring data quality on an ongoing basis to identify trends and issues that may affect data quality.
Data Governance: Developing and implementing data governance policies and procedures to ensure that data is managed effectively and efficiently.
Data Integration: Integrating data from various sources to ensure that data is accurate, complete, and consistent.
Communication: Communicating with stakeholders, such as data owners, data users, and IT teams, to understand data quality issues and implement solutions.
Reporting: Providing regular reports on data quality metrics, data quality trends, and data quality issues.
Continuous Improvement: Continuously improving data quality processes, tools, and methodologies to enhance data quality and ensure that data meets organizational needs.
Overall, the role of a Data Quality Analyst is critical in ensuring that data used by an organization is accurate, complete, and reliable. This requires a strong understanding of data quality concepts, data governance principles, and data management processes, as well as strong analytical, communication, and problem-solving skills.
What are the skills of a data quality analyst?
A Data Quality Analyst requires a combination of technical and soft skills to ensure that data used by an organization is accurate, complete, and reliable. Here are some of the key skills required for a Data Quality Analyst:
Data Analysis: The ability to analyze data to identify issues, anomalies, or errors that may affect data quality.
Data Cleansing: The ability to clean and standardize data to ensure consistency and completeness.
Data Validation: The ability to validate data to ensure that it meets defined quality standards, such as accuracy, completeness, and reliability.
Data Profiling: The ability to profile data to understand the data structure, data relationships, and data dependencies.
Data Governance: Knowledge of data governance policies and procedures to ensure that data is managed effectively and efficiently.
Technical Skills: Familiarity with data management tools and technologies, such as data profiling tools, data cleansing tools, and data integration tools.
Attention to Detail: The ability to pay close attention to detail to ensure that data quality is accurate and error-free.
Problem-Solving: The ability to identify and solve problems related to data quality issues.
Communication: Strong communication skills to effectively communicate with stakeholders, such as data owners, data users, and IT teams, to understand data quality issues and implement solutions.
Continuous Improvement: The ability to continuously improve data quality processes, tools, and methodologies to enhance data quality and ensure that data meets organizational needs.
Overall, a Data Quality Analyst requires a combination of technical expertise and soft skills, such as attention to detail, problem-solving, communication, and continuous improvement, to effectively ensure data quality and support organizational decision-making.