Data Quality Engineer
Tasks
- Analyze large-scale datasets
- Apply address standardization and validation
- Build data quality dashboards
- Build lookup validation rules
- Collaborate with ETL developers on data flows
- Configure alerting for quality threshold violations
- Configure exception handling and error routing
- Configure referential integrity checks
- Create technical dashboards with drill down
- Develop automated validation workflows
- Develop validation logic
- Document data quality test cases
- Execute attribute level validation
- Execute data profiling
- Execute real time data quality monitoring
- Implement data cleansing rules
- Implement data quality checkpoints in pipelines
- Implement data quality rules
- Maintain data quality runbooks
- Participate in defect triage
- Perform name parsing normalization
- Present data quality findings
- Support UAT activities
- Support data lineage documentation
- Test and validate rules in development and test
- Track data quality metrics
- Translate business requirements into validation rules
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Glue | Agile | Amazon Redshift | Apache Airflow | Azure | CI/CD | Cause analysis | Cloud platform | Data Cleansing | Data Governance | Data Normalization | Data Reconciliation | Data Standardization | Data Validation | Data profiling | Databricks | ELT | ETL | Git | Google Cloud | Google Cloud Platform | Great Expectations | Informatica | Pandas | Power BI | Pydeequ | Pytest | Python | Root Cause Analysis | Root cause | SQL | SQLAlchemy | Snowflake | Statistical Analysis | Tableau | Talend
Education
Roles
Data Quality | Data Quality Engineer | Engineer | Quality Engineer
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