QA Data Analyst

Murkez Technologies; Pakistan; Remote; PKR 1,800,000 - 2,800,000; Full time

Benefits offered by this job

Remote work

Job summary

Murkez Technologies is seeking an experienced QA Data Analyst to ensure data quality across our insurance data ecosystem. You will work with data engineers, actuaries, underwriters, and analysts to uphold data integrity for underwriting, claims processing, and regulatory reporting.

You will develop and execute data validation plans, implement automated quality checks, and mentor junior QA staff while aligning with compliance standards.

Qualifications

• Bachelor’s degree in Data Science, Computer Science, Information Systems, Actuarial Science, or a related field.
• 4+ years of experience in data QA, analytics, or engineering—ideally in the insurance or financial services industry.
• Advanced SQL skills with experience working on large-scale, complex data sets in insurance data environments.
• Hands-on experience with data quality frameworks, test automation tools, and scripting languages (e.g., Python).
• Understanding of insurance operations, data workflows, and compliance requirements.
• Actively communicate quality issues to internal/external stakeholders and document data issues.

Responsibilities

• Quality Assurance: Ensuring the quality and reliability of data analytics products through comprehensive testing strategies.
• Data Analysis: Conducting in-depth analysis to validate data integrity, accuracy, and insights generated by analytics processes.
• Collaboration: Working closely with developers, business teams, and other stakeholders to streamline testing efforts and improve overall product quality.
• Requirements and Documentation: Detailed communication of complex tasks and additional requirements, ensuring necessary information is included in documentation.
• Automation: Implementing and refining automation strategies for data processes, addressing issues like SQL timeouts to maintain system efficiency.
• Develop and execute comprehensive data validation and quality assurance plans for insurance data pipelines, including policy, claims, billing, and customer data.
• Perform data quality audits, identify anomalies, and lead root cause analysis efforts to ensure data consistency across systems.
• Design and implement automated data quality checks to support real-time and batch processing environments.
• Validate data feeds and transformations related to regulatory reporting, actuarial models, and risk management frameworks.
• Collaborate with cross-functional teams to define data quality metrics, business rules, and SLA thresholds for critical insurance datasets.
• Document test plans, QA findings, and remediation actions in alignment with compliance and audit standards (e.g., NAIC, HIPAA).
• Provide QA oversight on data projects involving underwriting systems, policy administration platforms, and claims processing workflows.
• Mentor junior QA analysts and advocate for best practices in data governance and quality control.

Skills

SQL

Python

Data quality

Test automation

Data analysis

Documentation

Communication

Education

Bachelor’s degree in Data Science/Computer Science/Information Systems/Actuarial Science

Master’s degree (preferred)

Tools

Python (scripting)

Job description

We are looking for an experienced and detail-driven QA Data Analyst to work on data quality initiatives within our insurance data ecosystem. This role is crucial to ensuring the accuracy, consistency, and regulatory compliance of data that drives underwriting, claims processing, risk analysis, and business reporting. You will collaborate closely with data engineers, actuaries, underwriters, and business analysts to ensure high standards of data integrity across operational and analytical systems.

Key Responsibilities:

• Quality Assurance: Ensuring the quality and reliability of data analytics products through comprehensive testing strategies.
  
• Data Analysis: Conducting in-depth analysis to validate data integrity, accuracy, and insights generated by analytics processes.
  
• Collaboration: Working closely with developers, business teams, and other stakeholders to streamline testing efforts and improve overall product quality.
  
• Requirements and Documentation: Detailed communication of complex tasks and additional requirements, ensuring necessary information is included in documentation.
  
• Automation: Implementing and refining automation strategies for data processes, addressing issues like SQL timeouts to maintain system efficiency.
  
• Develop and execute comprehensive data validation and quality assurance plans for insurance data pipelines, including policy, claims, billing, and customer data.
  
• Perform data quality audits, identify anomalies, and lead root cause analysis efforts to ensure data consistency across systems.
  
• Design and implement automated data quality checks to support real-time and batch processing environments.
  
• Validate data feeds and transformations related to regulatory reporting, actuarial models, and risk management frameworks.
  
• Collaborate with cross-functional teams to define data quality metrics, business rules, and SLA thresholds for critical insurance datasets.
  
• Document test plans, QA findings, and remediation actions in alignment with compliance and audit standards (e.g., NAIC, HIPAA).
  
• Provide QA oversight on data projects involving underwriting systems, policy administration platforms, and claims processing workflows.
  
• Mentor junior QA analysts and advocate for best practices in data governance and quality control.
  

This is a remote position.

We are looking for an experienced and detail-driven QA Data Analyst to work on data quality initiatives within our insurance data ecosystem. This role is crucial to ensuring the accuracy, consistency, and regulatory compliance of data that drives underwriting, claims processing, risk analysis, and business reporting. You will collaborate closely with data engineers, actuaries, underwriters, and business analysts to ensure high standards of data integrity across operational and analytical systems.

Key Responsibilities:

• Quality Assurance: Ensuring the quality and reliability of data analytics products through comprehensive testing strategies.
  
• Data Analysis: Conducting in-depth analysis to validate data integrity, accuracy, and insights generated by analytics processes.
  
• Collaboration: Working closely with developers, business teams, and other stakeholders to streamline testing efforts and improve overall product quality.
  
• Requirements and Documentation: Detailed communication of complex tasks and additional requirements, ensuring necessary information is included in documentation.
  
• Automation: Implementing and refining automation strategies for data processes, addressing issues like SQL timeouts to maintain system efficiency.
  
• Develop and execute comprehensive data validation and quality assurance plans for insurance data pipelines, including policy, claims, billing, and customer data.
  
• Perform data quality audits, identify anomalies, and lead root cause analysis efforts to ensure data consistency across systems.
  
• Design and implement automated data quality checks to support real-time and batch processing environments.
  
• Validate data feeds and transformations related to regulatory reporting, actuarial models, and risk management frameworks.
  
• Collaborate with cross-functional teams to define data quality metrics, business rules, and SLA thresholds for critical insurance datasets.
  
• Document test plans, QA findings, and remediation actions in alignment with compliance and audit standards (e.g., NAIC, HIPAA).
  
• Provide QA oversight on data projects involving underwriting systems, policy administration platforms, and claims processing workflows.
  
• Mentor junior QA analysts and advocate for best practices in data governance and quality control.
  

This is a remote position.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Information Systems, Actuarial Science, or a related field. Master’s degree is a plus.
  

• 4+ years of experience in data QA, analytics, or engineering—ideally in the insurance or financial services industry.
  

• Advanced SQL skills with experience working on large-scale, complex data sets in insurance data environments (e.g., policy, claims, rating data).
  

• Hands-on experience with data quality frameworks, test automation tools, and scripting languages (e.g., Python).
  

• Understanding of insurance operations, data workflows, and compliance requirements.
  

• Actively communicate to internal/external/stakeholders/customers quality issues about the way data is collected, stored, processed, or used
  
• Investigate, troubleshoot, and document data issues from internal and external customers
  
• Strong analytical, documentation and communication skills.
  

Preferred Qualifications:

• Experience with insurance core systems.
  

• Working knowledge of data privacy laws and regulatory frameworks applicable to insurance (e.g., HIPAA, NAIC MCAS).
  

• Exposure to data profiling and monitoring tools.
  

• Background in risk analysis, actuarial data, or predictive modeling QA is a strong plus.
  

• Experience working in Agile/Scrum environment