Senior Data Engineer Position

Tasks we expect you to fulfill:

• Build a BigQuery data warehouse for a global e-commerce brand unifying Shopify, Amazon, and ad platforms data
• Design an ETL pipeline pulling daily data from GA4, Meta Ads, and HubSpot into Microsoft Fabric for a B2B agency
• Set up automated data quality monitoring for a marketing agency processing 50+ client data feeds
   

What you will do:

• Build and maintain ETL / ELT pipelines from business APIs (Shopify, Amazon, GA4, ads platforms, CRMs, accounting tools)
• Design data models in BigQuery
• Set up scheduled data refreshes, error logging, and pipeline monitoring
• Run data quality checks: duplicates, missing values, broken joins, mismatched totals
• Document tables, fields, formulas, and assumptions clearly
• Collaborate with BI developers to prepare data for Power BI and Looker Studio

Required Skills:

• Strong SQL for data transformation, validation, and reporting logic
• Experience with Google Cloud Platform, especially BigQuery
• Building ETL / ELT pipelines from raw, messy business data
• API integration: Shopify, Amazon, GA4, ads platforms, CRMs, accounting tools
• Data quality checks and pipeline troubleshooting
• Git / version control
• Clear documentation
• English skills (B1-B2), both written & spoken
   

Bonus Skills:

• Microsoft data stack: Azure SQL, Microsoft Fabric, Dataflows, Power BI Service
• Understanding of how data should be prepared for Power BI / Looker Studio
• Python for data processing
   

Important! You must be able to showcase 2-4 past projects - ideally pipelines, data warehouses, or API integrations you've designed end-to-end. Be ready to walk us through the architecture, data quality decisions, and challenges you solved.

Salary:
30-45$ per hour