Back
Metro mid-level data role with generalist expectations but niche Cortex/Genie requirement reduces applicant pool.
Requires platform-specific Snowflake/Databricks Cortex/Genie and regulated-data governance experience, limiting cross-industry portability.
Explicit 5+ years, mandatory Cortex/Genie and governed data platform experience in a regulated environment.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
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.
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.
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.