Bachelor's degree in Computer Science, Information Systems, Analytics, Engineering, Statistics, Economics, or a related quantitative field; equivalent hands-on experience will be considered in lieu of a degree.
5+ years of experience building business intelligence and analytics solutions on a cloud data platform.
3+ years of advanced SQL in a production analytics environment.
3+ years of hands-on dbt experience building and maintaining production models.
3+ years of dashboard and report development in a modern BI tool;
Demonstrated experience gathering requirements directly from business stakeholders with limited direction or supervision.
Working experience with Google Cloud Platform, particularly BigQuery .
Proficiency with Python and with Git-based development workflows.
Advanced SQL, including complex analytical queries, window functions, and performance and cost optimization against columnar cloud warehouses.
Hands-on analytics engineering with dbt : modular models, tests, macros, snapshots, documentation, and deployment through CI/CD.
Working depth in at least one modern cloud data warehouse or lakehouse - BigQuery , Databricks, or equivalent - including partitioning, clustering, incremental strategies, and cost management.
Semantic layer development in LookML or an equivalent metrics modeling layer.
Dashboard and report development in a modern BI platform such as Looker , Power BI, or Tableau, with a strong grasp of visualization and information design principles.
Python for automation, data manipulation, and API integration.
Git-based version control and collaborative code review.
Databricks experience such as Unity Catalog, Delta Lake, SQL Warehouses, or PySpark.
Power BI experience including semantic models, DAX, Power Query, workspaces, and deployment pipelines.
Experience supporting Finance and Accounting analytics, such as revenue, billing, and margin reconciliation.
Industry background in logistics, transportation, e-commerce, or SaaS.
Experience working through a post-merger systems integration or a BI platform migration.
Experience with orchestration tooling such as Cloud Composer, Airflow, Dagster, or dbt Cloud.
Familiarity with Jira and Confluence for request intake and documentation.
Practical experience applying AI and LLM tooling to accelerate analytics development.