Data Quality Engineer
Tasks
- Build automated data quality checks
- Collaborate with data engineers to fix pipeline logic
- Define data quality standards
- Detect anomalies and schema drift
- Drive continuous improvement of data processes
- Implement alerting and reporting
- Investigate data quality issues at source
- Maintain data quality rubric
- Monitor data freshness and pipeline health
- Score data quality and report platform health
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Azure | Azure Functions | Azure Machine Learning | Azure OpenAI | Azure OpenAI Service | CCPA | Data Anomaly | Data Anomaly Detection | Data Governance | Data Monitoring | Data Observability | Data Quality | Data Validation | Data freshness | Data pipeline | Embeddings | GDPR | Langchain | Machine Learning | Model Serving | OpenAI Service | Prompt orchestration) | Schema drift | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Quality | Data Quality Engineer | Engineer | Quality Engineer
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