Intellypod · 11 hours ago
Data quality Engineer
United States
Contract
Remote
Senior Level
$40/hr - $45/hr
5+ years expIntellypod is seeking a Data Quality Engineer to ensure the integrity and reliability of enterprise data ingestion processes across critical healthcare platforms. This role involves establishing and maintaining data quality standards, validating data flows, and ensuring trusted information delivery to stakeholders.
Artificial Intelligence (AI)ConsultingSoftwareAppsComputer VisionMachine LearningNatural Language ProcessingWeb DesignWeb Development
Hiring Manager
Abdullah H Syed
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
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
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
Qualification
Required
5-7 years of experience with purely data projects
Ensuring the integrity and reliability of enterprise data ingestion processes
Establishing and maintaining data quality standards
Validating data flows
Ensuring data pipelines deliver trusted information to downstream consumers and business stakeholders
Validating ingested data against business rules, technical specifications, and quality standards
Conducting data profiling and analysis to identify quality issues, anomalies, and improvement opportunities
Performing data reconciliation activities to ensure accuracy and completeness across systems
Validating data transformations and dimensional modeling implementations
Monitoring data pipeline health and proactively identifying quality degradation or failures
Investigating and resolving data quality incidents including root cause analysis
Establishing alerting and notification mechanisms for quality issues
Documenting issues, patterns, and resolutions for continuous improvement
Tracking and reporting on data quality metrics, SLAs, and key performance indicators
Analyzing downstream impact of data quality issues on business operations
Generating quality reports and feedback mechanisms for rejected or problematic data
Collaborating with technical and business teams to define and refine quality requirements
Designing and implementing automated testing frameworks for data pipelines and ingestion processes
Developing comprehensive test strategies covering functional, performance, and regression scenarios
Building reusable validation utilities and quality check libraries
Company
Intellypod
AI driven platform development
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase