HonorVet Technologies
data quality engineer
HonorVet Technologies, Bentonville, Arkansas, United States, 72712
Job Title- data quality engineerReq Id- 131906Duration: 06+ MonthsRemote Role
ResponsibilitiesData Quality Assurance:
Conduct comprehensive analysis and profiling of master data sets to identify inconsistencies, inaccuracies, and anomalies related to our MDM solution.Identifying data cleansing and standardization processes to ensure data accuracy and consistency.Establish and maintain data quality metrics and KPIs to track and report on data quality performance.Identify data quality issues, perform root cause analysis, and recommend corrective actions to resolve these issues
Testing and Validation:
Design, develop, and execute detailed test plans, test cases, and test scripts for the MDM solution validation and verification.Conduct functional and non-functional testing to ensure that data quality requirements are met.Automate tests and integrate them into the pipeline to enhance efficiency and consistency in data validation.Perform regression testing to ensure that data quality remains intact after system changes or updates.
Collaboration:
Work closely with data stewards, data architects, and business analysts to define and understand data quality requirements and expectations related to the Master Data in the MDM solution.Collaborate with ED&I, IT, and business teams to resolve data quality issues and advise on long-term solutions.
Monitoring and Reporting:
Implement and maintain data quality monitoring and reporting to track MDM data quality issues and improvements.Develop dashboards and reports to visualize data quality metrics and provide insights to stakeholders.Continuously monitor data quality performance, identify trends, and drive continuous improvement initiatives.Document data quality issues, resolutions, and processes to ensure transparency and knowledge sharing across the team.Generate regular reports for management, highlighting key data quality metrics related to the Master Data solutions
QualificationsExperience:
Four (4) years of hands-on Data Quality and QA testing experienceExperience working in a Data Management, Data Quality, and/or Data QA function with a focus on MDM
Technical Skills:
Proven experience with Master Data Management (MDM) tools (custom, Informatica, Stibo, Reltio, etc).Proficiency in SQL and experience with data profiling and data quality tools (e.g., Informatica Data Quality, Talend, Bigeye, Collibra, Ataccama, etc).Hands-on experience in conducting data quality assessments, data cleansing, and data profiling.Experience with data visualization tools (e.g., Tableau, Power BI) for reporting and monitoring.Experience with scripting languages (e.g., Python, JavaScript) for test automation.Proficiency in testing automation and integrating automated tests into pipelines.Strong skills in designing and developing detailed test plans and test cases, and conducting functional, non-functional, and regression testing to ensure data quality
Analytical Skills:
Strong analytical and problem-solving skills with a keen eye for detail.Ability to analyze large datasets and identify data quality issues.Ability to perform root cause analysis and implement effective solutions to address data quality issues
ResponsibilitiesData Quality Assurance:
Conduct comprehensive analysis and profiling of master data sets to identify inconsistencies, inaccuracies, and anomalies related to our MDM solution.Identifying data cleansing and standardization processes to ensure data accuracy and consistency.Establish and maintain data quality metrics and KPIs to track and report on data quality performance.Identify data quality issues, perform root cause analysis, and recommend corrective actions to resolve these issues
Testing and Validation:
Design, develop, and execute detailed test plans, test cases, and test scripts for the MDM solution validation and verification.Conduct functional and non-functional testing to ensure that data quality requirements are met.Automate tests and integrate them into the pipeline to enhance efficiency and consistency in data validation.Perform regression testing to ensure that data quality remains intact after system changes or updates.
Collaboration:
Work closely with data stewards, data architects, and business analysts to define and understand data quality requirements and expectations related to the Master Data in the MDM solution.Collaborate with ED&I, IT, and business teams to resolve data quality issues and advise on long-term solutions.
Monitoring and Reporting:
Implement and maintain data quality monitoring and reporting to track MDM data quality issues and improvements.Develop dashboards and reports to visualize data quality metrics and provide insights to stakeholders.Continuously monitor data quality performance, identify trends, and drive continuous improvement initiatives.Document data quality issues, resolutions, and processes to ensure transparency and knowledge sharing across the team.Generate regular reports for management, highlighting key data quality metrics related to the Master Data solutions
QualificationsExperience:
Four (4) years of hands-on Data Quality and QA testing experienceExperience working in a Data Management, Data Quality, and/or Data QA function with a focus on MDM
Technical Skills:
Proven experience with Master Data Management (MDM) tools (custom, Informatica, Stibo, Reltio, etc).Proficiency in SQL and experience with data profiling and data quality tools (e.g., Informatica Data Quality, Talend, Bigeye, Collibra, Ataccama, etc).Hands-on experience in conducting data quality assessments, data cleansing, and data profiling.Experience with data visualization tools (e.g., Tableau, Power BI) for reporting and monitoring.Experience with scripting languages (e.g., Python, JavaScript) for test automation.Proficiency in testing automation and integrating automated tests into pipelines.Strong skills in designing and developing detailed test plans and test cases, and conducting functional, non-functional, and regression testing to ensure data quality
Analytical Skills:
Strong analytical and problem-solving skills with a keen eye for detail.Ability to analyze large datasets and identify data quality issues.Ability to perform root cause analysis and implement effective solutions to address data quality issues