Description

Design, develop, and optimize scalable data pipelines using Snowflake, dbt, SQL, and Python. Build and maintain data models, ETL/ELT workflows, and data transformation frameworks. Develop and optimize Snowflake data warehouses for performance, scalability, and cost efficiency. Create reusable dbt models, macros, tests, and documentation to support analytics and reporting. Collaborate with business, analytics, and engineering teams to gather and implement data requirements. Implement data quality, governance, monitoring, and lineage best practices. Integrate structured and unstructured data sources for analytics and AI/ML use cases. Support AI/ML initiatives by preparing feature datasets, enabling model training, and deploying data solutions. Develop and maintain APIs and data services to support AI/ML applications and automation. Troubleshoot production issues and optimize data platform performance. Strong experience with Snowflake, dbt, SQL, and Python. Hands-on experience building enterprise-scale ETL/ELT pipelines. Experience with data modeling, performance tuning, and query optimization. Knowledge of cloud platforms such as AWS, Azure, or GCP. Experience with CI/CD, Git, and Agile development practices. Understanding of data governance, security, and access controls

SKILLS_REQUIRED Snowflake, DBT, SQL, Python, AI/ML, GenAI, RAG, Vector Database ESSENTIAL_SKILLS Snowflake, DBT, SQL, Python, AI/ML, GenAI, RAG, Vector Database DESIRABLE_SKILLS UNIX, Control M, DataStage, FastAPI, Kafka, Airflow, Git, CI/CD

Key Skills

Education

Bachelor's degree