Senior Data Engineer – Data Quality & Observability
Tasks
- Build automated data validation checks
- Create data validation processes for quality dimensions
- Define and maintain data lineage
- Define validation frequency and remediation workflows
- Design and implement scalable data quality frameworks
- Develop reporting for quality trends
- Develop rule as code data quality rules
- Establish data governance and ownership practices
- Implement data observability with monitoring and alerting
- Implement data validation solutions
- Integrate data quality checks into CI/CD pipelines
- Investigate data issues with root cause analysis
Perks/Benefits
- Continuous improvement opportunities
- Cross-functional collaboration
- Fully remote work
- Ownership over data reliability strategy
Skills/Tech-stack
Alerting | Amazon Aurora | Amazon Aurora PostgreSQL | Amazon Redshift | Aurora PostgreSQL | CI/CD | Cause analysis | Dashboards | Data Governance | Data Lineage | Data Modeling | Data Observability | Data Quality | Data Validation | Data quality frameworks | ETL | Git | Great Expectations | Monitoring | Python | Quality frameworks | Referential Integrity | Root Cause Analysis | Root cause | Rule as Code | SQL | Soda | “as-code”
Education
N/A
Roles
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