Snowflake Data Engineer

Responsibilities

• Design, develop, and maintain robust data pipelines using Snowflake and ETL/ELT tools.
• Optimize Snowflake performance through query tuning, warehouse sizing, and data partitioning.
• Implement data modelling best practices (star/snowflake schema) for analytics and reporting.
• Integrate Snowflake with various data sources including cloud storage (S3, Azure Blob), APIs, and third-party platforms.
• Automate data ingestion using Snow pipe, Streams, and Tasks.
• Ensure data quality, integrity, and security across all pipelines.
• Collaborate with data analysts, scientists, and business stakeholders to understand data requirements.
• Monitor and troubleshoot data pipeline issues and ensure timely resolution.
• Document technical designs, data flows, and operational procedures.
• Setup and Manage roles and privileges of the latest trends and technologies in DevOps and introduce new service offerings from the DevOps COE.
  

Required Skills

• 5+ years of experience in data engineering, with at least 2+ years working with Snowflake.
• Strong proficiency in SQL and Snowflake SQL features.
• Hands-on experience with ETL/ELT tools such as dbt, Airflow, Talend, or Informatica.
• Proficiency in Python or Scala for data processing and scripting.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Solid understanding of data warehousing concepts and data modeling.
• Familiarity with CI/CD pipelines, version control (Git), and DevOps practices.
• Knowledge of data governance, RBAC, and security best practices.
• Excellent problem-solving, communication, and collaboration skills.
  

Preferred Qualifications

• Snowflake certifications (SnowPro Core or Advanced).
• Exposure to real-time data processing and streaming technologies.
• Experience in Agile/Scrum environments.