Analytics Engineering — The Role Between Data and Business

Analytics engineering builds reliable data models that enable self-serve analytics. It serves as a bridge between raw data and business insights.

What Does an Analytics Engineer Do¶

Transforms raw data into business-ready models.

Responsibilities¶

• Data modeling — star schema, OBT
• dbt transformations — SQL models
• Data quality — monitoring
• Documentation — glossaries, lineage
• Metrics — KPIs as code

Semantic Layer¶

# dbt Semantic Layer
semantic_models:
  - name: orders
    model: ref('fct_orders')
    measures:
      - name: revenue
        agg: sum
        expr: total_czk
metrics:
  - name: average_order_value
    type: derived
    type_params:
      expr: revenue / order_count

Stack¶

• Transformations: dbt
• Warehouse: Snowflake, BigQuery, DuckDB
• BI: Metabase, Superset, Looker

Summary¶

Analytics engineering is the bridge between data and business. dbt and the semantic layer form the foundation of self-serve analytics.