Primary Responsibilities

• Design, build, and maintain robust ELT pipelines on the Snowflake data platform to handle large datasets efficiently.
• Collaborate with data architects, analysts, and other stakeholders to ensure data pipelines meet business requirements and objectives.
• Write efficient and optimized SQL queries for data extraction, transformation, and loading.
• Develop and maintain automated workflows using dbt, Python, and orchestration tools (e.g., Airflow, Prefect, etc.).
• Ensure data pipeline reliability, scalability, and performance across different environments.
• Monitor and troubleshoot pipeline performance, addressing data quality issues and resolving failures quickly.
• Stay updated on the latest features and best practices within the Snowflake ecosystem to continuously improve system performance.
• Participate in code reviews, providing guidance on best practices and optimizing existing processes.
• Contribute to the improvement of the overall data engineering framework and architecture.

Required Skills and Qualifications

• 6+ years of experience in data engineering and 4+ years specifically in cloud data warehousing (Snowflake preferred).
• Expertise in Snowflake architecture, performance tuning, and ELT pipeline design.
• Strong proficiency in SQL for querying and managing large datasets.
• Hands-on experience with dbt (Data Build Tool) for data transformations.
• Advanced Python skills for data processing and pipeline automation.
• Proficiency with orchestration tools such as Apache Airflow, Prefect, or similar.
• Snowflake SnowPro Core Certification (mandatory).
• Strong analytical and troubleshooting skills for resolving complex data issues.
• Familiarity with cloud platforms like AWS, Azure, or GCP.
• Knowledge of data warehousing concepts, data modeling, and ETL processes.

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