Azure Data Engineer

Description

Azure Data Engineer - Retail Media

Main Skill:

DATA

Domain Skills:

AZURE, DATA, PYTHON

Nice to Have Skills:

JAVA

Responsibilities

• Ingestion and Integration: Collect data from advertising campaigns (impressions, clicks, conversions) and cross-reference it with transactional data.

• Modeling and Organization: Structure data for performance analysis, attribution and monetization.

• Data Pipelines: Develop ETL/ELT in Azure Data Factory, Databricks, and Delta Lake.

• Streaming and Near Real-Time: Implement solutions for high-frequency event ingestion (Kafka, Event Hub).

• Quality and Governance: Ensure compliance with LGPD/GDPR, anonymization and lineage with Unity Catalog.

• Integration with Analytics Platforms and AdTech: Prepare data for Analytics Team (BI) and activation environments (DSPs, CDPs, Data Clean Rooms).

Technical Skills

• Cloud: MS Azure (Data Lake, Data Factory, Key Vault).

• Big Data: Databricks (Py Spark, Delta Lake).

• Languages: Python, SQL.

• Governança: Unity Catalog, LGPD/GDPR.

• Orchestration: Azure Data Factory

• CI/CD: Git, Azure DevOps.

• Monitoring: Log Analytics, alerts.

Differentials

Specific Knowledge of Retail Media

• Ecossistema AdTech/Mar Tech: DSP, SSP, Ad Servers, DMPs, CDPs.

• Digital média metrics: CTR, CPC, ROAS, impressions, clicks, conversions.

• Attribution models: Last-click, multi-touch, incrementality.

• Ad platform APIs: Google Ads, Criteo, The Trade Desk, Amazon Ads.

• Privacy applied to advertising: Consent, anonymization, digital IDs (cookies, device IDs, hashed emails).

• Data Clean Rooms: Concept and integration for secure data sharing.