Location: Remote
Duration: Contract (12+ months, potential for extension)
We are seeking a Data Engineer with strong expertise in Google Cloud Platform (GCP), BigQuery, and SQL, along with experience supporting retail data environments.
This role will focus on building and optimizing data pipelines that support store operations, merchandising, inventory, supply chain, and sales analytics within a large-scale retail organization. The ideal candidate brings a strong engineering mindset and hands-on experience working with high-volume, enterprise retail datasets.
Design, develop, and optimize data pipelines and ELT processes using BigQuery and GCP services
Write and tune complex, high-performance SQL queries across large-scale retail datasets
Build and maintain data models supporting merchandising, inventory, supply chain, and store performance reporting
Ingest and transform data from retail systems (POS transactions, product hierarchy, inventory levels, pricing, promotions)
Partner with business stakeholders (merchants, supply chain, finance, store operations) to deliver scalable data solutions
Ensure data quality, governance, and consistency across enterprise data platforms
Optimize performance and cost efficiency within BigQuery and GCP environments
4+ years of experience in Data Engineering
Strong hands-on experience with BigQuery
Advanced proficiency in SQL (complex joins, window functions, performance tuning)
Experience working within Google Cloud Platform (GCP)
Experience supporting retail data environments (POS, merchandising, inventory, supply chain, pricing, promotions)
Strong understanding of data modeling, ETL/ELT, and large-scale data processing
Experience with Python for data processing or automation
Familiarity with data orchestration tools (e.g., Airflow)
Experience working with enterprise data warehouses (EDW)
Exposure to BI/analytics tools (Looker, Tableau, etc.)
Experience in large-scale or Fortune 500 retail environments
Engineers who understand retail data complexity (high volume, seasonality, product hierarchies, store-level variability)
Strong ownership mindset with the ability to deliver end-to-end data solutions
Ability to operate in complex, cross-functional enterprise environments
Strong communication skills to bridge technical teams and business stakeholders

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