Senior Data Engineer – Data Quality & Observability
Tasks
- Build automated validation checks for datasets and workflows
- Create validation for completeness accuracy integrity consistency reconciliation freshness and anomaly detection
- Define governance ownership and remediation workflows
- Design and implement scalable data quality frameworks
- Develop data quality reporting and health metrics dashboards
- Develop data quality rules with Rule as Code
- Implement data observability monitoring alerting and dashboards
- Improve data engineering practices for reliable data systems
- Integrate data validation into CI/CD pipelines
- Lead data validation using Great Expectations
- Maintain data lineage across business areas
- Perform root cause analysis for recurring data issues
Perks/Benefits
- Collaboration with cross-functional teams
- Exposure to modern data validation frameworks and observability technologies
- Fully remote work
- Opportunities for continuous improvement
- Ownership over data reliability strategy
Skills/Tech-stack
Alerting | Amazon Redshift | Aurora PostgreSQL | CI/CD | Cause analysis | Dashboards | Data Governance | Data Lineage | Data Modeling | Data Observability | Data Validation | ETL | Git | Great Expectations | Monitoring | Root Cause Analysis | Root cause | Rule as Code | SQL | Soda | “as-code”
Education
N/A
Roles
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