About the role
Introduction As a Quality Engineer specializing in data, you will play a critical role in ensuring the quality, accuracy, and integrity of our data-driven applications and services. Your primary responsibilities will include data validation, data quality improvement, and the development and maintenance of data-related testing strategies, methodologies, and tools.
Your Role And Responsibilities As a Quality Engineer specializing in data, you will play a critical role in ensuring the quality, accuracy, and integrity of our data-driven applications and services. Your primary responsibilities will include data validation, data quality improvement, and the development and maintenance of data-related testing strategies, methodologies, and tools.
Key Responsibilities
- Data Validation and Quality Improvement:
- Design, develop, and execute comprehensive data validation strategies and methodologies.
- Collaborate with data engineers, data scientists, and other stakeholders to ensure data accuracy, completeness, and consistency.
- Identify and address data quality issues, including data cleansing, transformation, and enrichment.
- Data Testing Strategy and Planning:
- Define and document data testing strategies, test plans, scope, schedule, and entry/exit criteria.
- Align data testing with business goals, project objectives, and regulatory requirements.
- Break down data testing scope into manageable units and map them to data-related business priorities.
- Test Data Management:
- Define and implement test data management strategies, including data provisioning, masking, and refresh.
- Ensure the availability, security, and compliance of test data across various environments.
- Data-related Compliance and Regulatory Projects:
- Collaborate with compliance teams to ensure data testing processes, tools, and artifacts meet regulatory requirements (e.g., GDPR, HIPAA, or other industry-specific standards).
- Stay updated on data-related industry regulations and standards relevant to our business domain.
- Cross-functional Collaboration:
- Work closely with data engineers, data scientists, developers, product owners, and other stakeholders to ensure alignment on data requirements, design, and testing objectives.
- Facilitate regular communication, status updates, and risk discussions with cross-functional teams.
- Test Automation and Optimization:
- Lead the development, maintenance, and enhancement of data-related automation frameworks and tools.
- Promote the adoption and continuous improvement of data testing automation, including data-driven testing, data validation, and data transformation.
- Reporting and Communication:
- Prepare and present data testing progress, performance metrics, and recommendations to executive leadership and cross-functional teams.
- Generate detailed test reports, defect summaries, and risk assessments related to data quality and testing.
- Risk Management and Compliance:
- Identify, assess, and prioritize data-related risks based on their potential impact on project objectives and stakeholders.
- Develop and implement risk mitigation strategies and contingency plans.
- Continuous Learning and Growth:
- Encourage a culture of continuous learning and improvement within the data testing function.
- Represent the data testing team in knowledge-sharing sessions, workshops, and industry events.
Preferred Education Bachelor's Degree
Required Technical And Professional Expertise
- 5+ years of experience in quality engineering, with a strong focus on data testing and validation.
- Proven track record of leading and managing data testing teams within an enterprise environment.
- Thorough understanding of data management principles, data modeling, and data architecture.
- In-depth knowledge of data testing methodologies, tools, and best practices.
- Strong proficiency in SQL and data manipulation languages (e.g., Python, R, or Scala).
- Experience with data testing frameworks and tools (e.g., Apache NiFi, Talend, or Informatica).
- Knowledge of data-related industry standards and regulations (e.g., GDPR, HIPAA, or PCI DSS).
- Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) and big data technologies
About IBM
At IBM, we do more than work. We create. We create as technologists, developers, and engineers. We create with our partners. We create with our competitors. If you're searching for ways to make the world work better through technology and infrastructure, software and consulting, then we want to work with you.
We're here to help every creator turn their "what if" into what is. Let's create something that will change everything.
About the role
Introduction As a Quality Engineer specializing in data, you will play a critical role in ensuring the quality, accuracy, and integrity of our data-driven applications and services. Your primary responsibilities will include data validation, data quality improvement, and the development and maintenance of data-related testing strategies, methodologies, and tools.
Your Role And Responsibilities As a Quality Engineer specializing in data, you will play a critical role in ensuring the quality, accuracy, and integrity of our data-driven applications and services. Your primary responsibilities will include data validation, data quality improvement, and the development and maintenance of data-related testing strategies, methodologies, and tools.
Key Responsibilities
- Data Validation and Quality Improvement:
- Design, develop, and execute comprehensive data validation strategies and methodologies.
- Collaborate with data engineers, data scientists, and other stakeholders to ensure data accuracy, completeness, and consistency.
- Identify and address data quality issues, including data cleansing, transformation, and enrichment.
- Data Testing Strategy and Planning:
- Define and document data testing strategies, test plans, scope, schedule, and entry/exit criteria.
- Align data testing with business goals, project objectives, and regulatory requirements.
- Break down data testing scope into manageable units and map them to data-related business priorities.
- Test Data Management:
- Define and implement test data management strategies, including data provisioning, masking, and refresh.
- Ensure the availability, security, and compliance of test data across various environments.
- Data-related Compliance and Regulatory Projects:
- Collaborate with compliance teams to ensure data testing processes, tools, and artifacts meet regulatory requirements (e.g., GDPR, HIPAA, or other industry-specific standards).
- Stay updated on data-related industry regulations and standards relevant to our business domain.
- Cross-functional Collaboration:
- Work closely with data engineers, data scientists, developers, product owners, and other stakeholders to ensure alignment on data requirements, design, and testing objectives.
- Facilitate regular communication, status updates, and risk discussions with cross-functional teams.
- Test Automation and Optimization:
- Lead the development, maintenance, and enhancement of data-related automation frameworks and tools.
- Promote the adoption and continuous improvement of data testing automation, including data-driven testing, data validation, and data transformation.
- Reporting and Communication:
- Prepare and present data testing progress, performance metrics, and recommendations to executive leadership and cross-functional teams.
- Generate detailed test reports, defect summaries, and risk assessments related to data quality and testing.
- Risk Management and Compliance:
- Identify, assess, and prioritize data-related risks based on their potential impact on project objectives and stakeholders.
- Develop and implement risk mitigation strategies and contingency plans.
- Continuous Learning and Growth:
- Encourage a culture of continuous learning and improvement within the data testing function.
- Represent the data testing team in knowledge-sharing sessions, workshops, and industry events.
Preferred Education Bachelor's Degree
Required Technical And Professional Expertise
- 5+ years of experience in quality engineering, with a strong focus on data testing and validation.
- Proven track record of leading and managing data testing teams within an enterprise environment.
- Thorough understanding of data management principles, data modeling, and data architecture.
- In-depth knowledge of data testing methodologies, tools, and best practices.
- Strong proficiency in SQL and data manipulation languages (e.g., Python, R, or Scala).
- Experience with data testing frameworks and tools (e.g., Apache NiFi, Talend, or Informatica).
- Knowledge of data-related industry standards and regulations (e.g., GDPR, HIPAA, or PCI DSS).
- Familiarity with cloud platforms (e.g., AWS, Azure, or Google Cloud) and big data technologies
About IBM
At IBM, we do more than work. We create. We create as technologists, developers, and engineers. We create with our partners. We create with our competitors. If you're searching for ways to make the world work better through technology and infrastructure, software and consulting, then we want to work with you.
We're here to help every creator turn their "what if" into what is. Let's create something that will change everything.