Job Title-
Data Analyst/Data Quality Engineer
You will work at the intersection of data engineering,
quality assurance, and business analysis—translating technical data flows into
business value while ensuring accuracy, completeness, and reliability across
our data ecosystem.
Key Responsibilities
- Validate ingested data
against business rules, technical specifications, and quality standards
- Conduct data profiling
and analysis to identify quality issues, anomalies, and improvement
opportunities
- Perform data
reconciliation activities to ensure accuracy and completeness across
systems
- Validate data
transformations and dimensional modeling implementations
- Design and implement
automated testing frameworks for data pipelines and ingestion processes
- Develop comprehensive
test strategies covering functional, performance, and regression scenarios
- Build reusable
validation utilities and quality check libraries
- Ensure testing
frameworks align with CI/CD practices and engineering standards
- Monitor data pipeline
health and proactively identify quality degradation or failures
- Investigate and resolve
data quality incidents including root cause analysis
- Establish alerting and
notification mechanisms for quality issues
- Document issues,
patterns, and resolutions for continuous improvement
- Track and report on data
quality metrics, SLAs, and key performance indicators
- Analyze downstream
impact of data quality issues on business operations
- Generate quality reports
and feedback mechanisms for rejected or problematic data
- Collaborate with
technical and business teams to define and refine quality requirements
Skills Required
- Ensure integrity and reliability of enterprise data ingestion processes
- Validate ingested data against business rules, technical specifications, and quality standards
- Conduct data profiling and analysis to identify quality issues and anomalies
- Perform data reconciliation activities to ensure accuracy and completeness across systems
- Validate data transformations and dimensional modeling implementations
- Design and implement automated testing frameworks for data pipelines and ingestion processes
- Develop comprehensive test strategies covering functional, performance, and regression scenarios
- Build reusable validation utilities and quality check libraries
- Ensure testing frameworks align with CI/CD practices and engineering standards
- Monitor data pipeline health and proactively identify quality degradation or failures
- Investigate and resolve data quality incidents including root cause analysis
- Establish alerting and notification mechanisms for quality issues
- Track and report on data quality metrics, SLAs, and KPIs
- Collaborate with technical and business teams to define and refine quality requirements
What We Do
Genzeon advances highly effective, secure, and innovative technology solutions for healthcare and retail clients, including intelligent automation, security, compliance, and cloud services. Founded in 2009, by a group of leaders with a shared commitment to unleashing human potential, Genzeon is blazing new trails in fueling innovation, transforming businesses and unleashing efficiency. Our vision is to Dream Big, Deliver Excellence

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