Snowflake Data Engineer

Key Responsibilities

• Data Integration & Extraction
• Develop and maintain ETL/ELT pipelines using Airbyte and Airflow.
• Extract data from multiple sources including APIs, direct database connections, and flat files.
• Ensure data quality, consistency, and reliability across all ingestion processes.
• Data Modeling & Warehousing
• Design and implement Kimball-style dimensional models in Snowflake.
• Build and optimize fact tables and dimension tables to support analytical workloads.
• Collaborate with business teams to define and maintain the BUS Matrix for subject areas.
• Transformation & Orchestration
• Use DBT to develop modular, testable, and version-controlled transformations.
• Implement data quality checks and documentation within DBT workflows.
• Collaboration & Governance
• Work closely with business stakeholders to understand requirements and translate them into technical solutions.
• Ensure compliance with data governance, security, and privacy standards.

Required Skills & Qualifications

• Technical Expertise
• Strong proficiency in Snowflake architecture and performance tuning.
• Hands-on experience with DBT, Airbyte, and Airflow.
• Solid understanding of Kimball methodology for data warehousing.
• Programming & Querying
• Advanced SQL skills and familiarity with Python for ETL scripting.
• Experience integrating data from APIs and relational databases.
• Soft Skills
• Excellent communication and collaboration skills.
• Ability to work in an agile environment and manage multiple priorities.

Preferred Qualifications

• Experience with cloud platforms (AWS, Azure, or GCP).
• Familiarity with BI tools (e.g., Tableau, Power BI).
• Knowledge of data governance and security best practices.