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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and operate AI-ready data products and semantic layers on Snowflake and/or Databricks enabling governed natural-language querying for Finance business users.
Deploy and optimize Snowflake Cortex or Databricks Genie spaces with Unity Catalog for accuracy, adoption, and business value.
Engineer ETL/ELT pipelines and implement data governance (RBAC, RLS, masking, lineage) in regulated pharma environment while managing cost and performance.
Minimum Requirements
5+ years hands-on data engineering experience on cloud platforms like Snowflake and/or Databricks with delivered projects.
Direct production experience with Snowflake Cortex or Databricks Genie spaces (specific components like Cortex Analyst, Search, Agents, LLM Functions).
Strong skills in semantic layer/trusted data product delivery, including KPIs, hierarchies, business glossary alignment.
Proficiency in dbt, PySpark, Snowpark, SQL, Python, and orchestration tools like Airflow or Databricks Workflows; data governance experience in regulated environments.
Ideal Candidate Profile
Experienced in building governed data products integrated into AI-enablement workflows rather than pure model building or data science roles.
Strong foundation in modern cloud data platform engineering combined with operational deployment of semantic and AI query layers.
Comfortable working with regulated pharma data and partnering closely with Finance domain stakeholders to translate requirements into data solutions.