Senior AI Solutions Engineer

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Description

Required Qualifications Core Programming & Tooling · Strong programming proficiency in Python, producing production-quality, well-structured code. · Proficient in SQL; experience with large-volume datasets in Spark and/or Snowflake. · Comfortable scripting in Python and Bash for automation and tooling. · Expertise with Git for version control, branching strategies, code review, and pull request workflows. · Familiarity with experiment tracking and model versioning (e.g., MLflow). Snowflake · Data lake vs data warehouse architecture (medallion architecture: bronze/silver/gold) · API integration patterns for ingesting from source systems · Schema evolution and handling semi-structured data · Advanced SQL (window functions, CTEs, recursive queries, semi-structured data with VARIANT/JSON) · Warehouse sizing, scaling, and cost optimization · Data sharing, Time Travel, Zero-Copy Cloning · Snowpipe for streaming/continuous ingestion · Role-based access control (RBAC), security, and data governance · Query performance tuning (clustering keys, micro-partitions, query profiling) · Streams and Tasks for CDC and orchestration · Snowpark (Python/Java integration) is increasingly valuable · Model development (staging/intermediate/mart layers) · Jinja templating, macros, and incremental models · Snapshots for SCD Type 2 · dbt testing (schema tests, dbt-utils) · Version control: Git/GitHub or Azure Repos, branching strategies · Orchestration: Airflow, Azure Data Factory, or Dagster · Data mo

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