Skills Required

• SAP data extraction: OData services, RFC/BAPI, SAP Data Services, or CDS views — hands-on experience pulling data from SAP FI/CO modules
• Python — async data pipelines, background jobs, scheduled tasks
• PostgreSQL — schema design, migrations (Alembic), query optimization, partitioning
• Azure Data Lake Storage + Synapse Analytics
• Microsoft Graph API — SharePoint, M365, organizational data
• Apache Airflow or Azure Data Factory
• dbt or equivalent for transformation and quality testing
• Redis — queue management, TTL, cache invalidation
• Observability — structured logging, Azure Monitor or Prometheus/Grafana
• Docker — containerized pipeline jobs
• Infrastructure-as-code (Terraform or equivalent)
  
  Has designed and built a data platform from scratch in an enterprise environment — not inherited a running system, built one. Has pulled data from SAP or comparable ERP into a warehouse and survived upstream failures without silent data loss. Sets standards that other engineers can follow without three clarification meetings. Can make architecture calls quickly and correct them later. Has strong opinions about pipeline observability and data quality.