Director, Customer Success Data Engineering
Tasks
- Build documentation layer for AI data access
- Collaborate on KPI definitions data lineage and governance
- Define AI data strategy for customer success
- Design and optimize analytics data pipelines
- Design data integration for contact center platform migration
- Establish data delivery SLAs and data quality monitoring
- Implement testing monitoring and alerting for data pipelines
- Lead and mentor data and analytics engineers
- Redesign unified customer success data model
- Translate business problems into data architecture decisions
Perks/Benefits
Skills/Tech-stack
AI Data | AI data strategy | AI retrieval | Airflow | Anomaly Detection | BI Dashboards | DBT | Data Architecture | Data Freshness Monitoring | Data Governance | Data Lineage | Data Modeling | Data Pipelines | Data Quality | Data Testing | Data completeness | Data completeness validation | Data freshness | Data integration | Data quality monitoring | Data strategy | ETL | Freshness Monitoring | KPI Dictionary | Kafka | Kinesis | Quality monitoring | Schema Validation | Semantic layer | Snowflake
Education
N/A
Regions
Countries
States
Cities
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