Senior Data Platform Engineer
Tasks
- Build ingestion pipelines
- Build serving pipelines
- Build transformation pipelines
- Define CI CD practices for data systems
- Define data standards
- Define dataset SLOs and SLAs
- Deliver reusable datasets
- Design data platform architecture
- Enforce data modeling standards
- Ensure audit and compliance
- Handle PII data
- Handle incidents
- Implement data governance
- Implement data observability
- Manage RBAC access
- Manage data contracts
- Manage metadata
- Monitor data quality
- Monitor orchestration workflows
- Own lakehouse and warehouse architecture
- Run batch processing pipelines
- Run streaming processing pipelines
- Set data retention policies
- Track dataset completeness
- Track dataset freshness
- Track dataset latency
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Alation | Amazon Kinesis | Apache Airflow | Apache Flink | Apache Hudi | Apache Iceberg | Apache Kafka | Auditability | Azure | Azure Event | Azure Event Hubs | Batch Processing | CI/CD | Collibra | Containerization | DBT | Dagster | Data Contracts | Data Governance | Data Lake | Data Lineage | Data Modeling | Data Observability | Data Quality | Data Retention | Data Warehouse | Data pipeline | Datahub | Delta Lake | Event Hubs | Great Expectations | Infrastructure as Code | Kubernetes | Lakehouse | Looker | Metadata | Microsoft Purview | PII | Power BI | Prefect | Python | RBAC | SQL | Schema management | Soda | Spark Streaming | Streaming processing | Tableau | Terraform | Unity Catalog | “as-code”
Education
N/A
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