Data Analytics Engineering

Scope

• Define metrics, grains, and dimensional models.
• Build transformation layers and semantic models.
• Implement data quality tests and observability.
• Document datasets, lineage, and ownership.
• Align analytics outputs with BI and product needs.

Ask For Inputs

• Business metrics and decision use cases.
• Source systems, data freshness, and latency needs.
• Existing warehouse, tooling, and orchestration.
• Expected data volumes and change cadence.
• Governance requirements and access controls.

Workflow