Data Engineers

Core Technical Skills

• Advanced SQL (Snowflake, Databricks): Table management, deprecation, data querying
• Python: Scripting for automation, ETL workflows, alert tooling
• Airflow: DAG creation, dependency management, alert tuning
• Version Control & CI/CD: Git, deployment pipelines, code reviews

Monitoring & Observability

• Monte Carlo (MC): Alert configuration, suppression, false positive reduction
• Observability Tooling: Integration with Airflow, Datadog, or similar tools
• Root Cause Analysis: Debugging alert triggers and noisy pipelines

Platform Migration & Pipeline Stability

• Legacy to Modern Platform Migration: (e.g., RDE → Alchemist or Data Infra)
• Upstream Dependency Debugging: Identify and resolve R+ or external data source failures
• Pipeline Ownership Handoff: Documentation, transfer of Gold and People Analytics pipelines

Process & Documentation

• Technical Documentation: Wikis, runbooks, alert resolution docs
• Cross-team Collaboration: Working with FDE, Data Infra, Storefront, CX, GCO
• Data Governance Awareness: Ownership models, process compliance, alert accountability

Data Infrastructure Hygiene

• Table Deprecation & Cleanup: Snowflake, Salesforce, unused pipelines
• Alert Consolidation: Eliminate redundant monitors and streamline alerting logic