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We’re looking for a talented, experienced, and quality-driven Senior BI Developer to join our growing team and help shape the foundation of our data platform. This position is a key role within Global-e’s Data Department, which supports critical business decisions and manages complex processes. You will help power a global cross-border e-commerce platform handling millions of transactions and enabling data-driven decisions.
Job Responsibility:
Design, build, and maintain scalable BI dashboards and reports using internal cutting edge AI LLM solution
Design, build, and maintain scalable ELT pipelines to ingest, transform, and load data from diverse sources into the data warehouse
Develop and maintain data models using dbt for transformation and Rivery Qlik Replicate for ingestion, ensuring data quality, consistency, and documentation
Build and manage data infrastructure in Snowflake, including schemas, roles, access control, and performance optimization
Collaborate with analysts, data scientists, and business stakeholders to deliver reliable, well-structured data products supporting BI and ML workloads
Write clean, maintainable Python scripts for data processing, orchestration, and automation
Monitor pipeline health, troubleshoot issues, and drive continuous improvements to reliability and performance
Define and enforce data engineering best practices — including testing, CI/CD, versioning, and documentation
Requirements:
5+ years of experience in BI Development or a closely related role
Experience with BI tools such as Tableau, Looker, Power BI, or QlikSense
Hands-on experience with Snowflake or an equivalent cloud data warehouse (BigQuery, Redshift, Databricks)
Experience designing and maintaining data models (dimensional, OBT, or similar) for analytical workloads
Experience with leverage AI capabilities (e.g., LLMs or predictive models) to enhance analytics, such as generating automated insights, natural language querying, anomaly detection, semantic models design & development
Familiarity with orchestration tools such as Apache Airflow or equivalent
Strong understanding of data quality, testing practices, and observability
Ability to work independently and collaborate effectively in a cross-functional environment
Nice to have:
Solid Python programming skills for pipeline scripting, API ingestion, and data validation
Exposure to ML engineering or feature store concepts