AI-Enabled Data Engineer

📋 Description Design, build, and maintain scalable data pipelines across cloud and on-prem. Work with Snowflake, Databricks, and Delta Lake as primary data platforms. Model data with dbt: modular SQL, manage dependencies, and contracts. Build semantic layers for governed metrics used by downstream consumers. Design data warehouse schemas and data lakes for performance and cost. Implement data quality: testing, validation, alerting, and lineage in pipelines. 🎯 Requirements ETL/ELT design, data modeling, quality/testing, lineage, batch & incremental loads. Snowflake, Databricks, Spark/PySpark, Delta Lake, data warehouses and data lakes. dbt Core / dbt Cloud, SQL advanced, semantic layer, dimensional modeling. Airflow, Dagster/Prefect, Azure Data Factory, Databricks Workflows. RAG & vector pipelines, AI-augmented ETL, MCP/agent tools, LLM integration. AWS S3/Glue/Redshift; Azure ADLS/ADF/Synapse; CI/CD for data; IaC. 🎁 Benefits Work on real, complex data problems across client environments. A team that takes AI tooling seriously and expects you to use it. Access to the full modern data stack — no one-tool shops. Room to grow into data architecture, platform leadership, or AI engineering. Collaborative culture that values opinions, craft, and intellectual curiosity.