Design, build, and maintain production-grade data models to bridge raw data streams with downstream
Use LLMs and AI tools to generate data documentation, write SQL/Python transformations, convert
Standardize data modeling practices and build robust, reliable, scalable semantic layers
Lead scoping discussions with product, tech and finance stakeholders to translate business
Reconcile data definitions across departments
Establish automated testing, monitoring, and data quality frameworks

🎯 Requirements

5+ years of experience in Data Engineering, Analytics Engineering, or Data Science, with at least 2
Advanced SQL capabilities
Hands-on expertise with modern data transformation and orchestration frameworks (dbt, Airflow
Deep experience with cloud data warehouses (Snowflake, Databricks, BigQuery)
Understanding of feature engineering, AI agentic workflow lifecycles, and evaluation metrics
Experience with deploying AI agentic workflows in production environments

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