Description:

Design, build, and operate trusted datasets, semantic models, and embedded AI experiences for Finance.
Focus on engineering the data foundation for reliable AI, including semantic layers and governed data products.

Requirements:

5+ years of hands-on data engineering experience on cloud data platforms, specifically Databricks.
Direct experience with Databricks Genie, including building and tuning in production.
Proven delivery of semantic layers and trusted data products with KPI definitions and business glossary alignment.
Proficiency in dbt, PySpark, SQL, and Python.
Experience with orchestration tools like Airflow or Databricks Workflows.
Knowledge of data governance in regulated environments, including RBAC and auditability.
Ability to integrate structured and unstructured data into AI workflows.

Opportunity to work in a cutting-edge AI-enablement project within a regulated environment.
Collaborate with Finance business stakeholders to create impactful data solutions.

Skills