Data Analytics Engineer

Design, develop, and maintain scalable data pipelines and Snowflake data warehouse models. Implement data ingestion processes using Snowflake and ETL/ELT tools (e.g., dbt, Informatica, Talend, etc.). Optimize Snowflake SQL queries and manage performance tuning and data modeling. Develop and maintain stored procedures, UDFs, and other Snowflake scripting components. Work with cross-functional teams to understand business requirements and translate them into technical solutions. Collaborate with BI developers to provide clean, transformed, and well-modeled data for analytics and reporting. Maintain data governance, security, and compliance within the Snowflake environment. Monitor data pipelines for reliability and troubleshoot issues as needed. Support integration of Snowflake with various data sources and analytics tools like Tableau, Power BI, Looker, etc. Required Skills and Qualifications: 6 to 8 years of experience in data engineering, data warehousing, or data analytics roles. Minimum 3+ years of hands-on experience with Snowflake (data modeling, performance tuning, schema design, etc.). Strong proficiency in SQL, with expertise in writing complex queries and stored procedures. Solid experience with ETL/ELT tools and frameworks. Familiarity with cloud platforms (AWS, Azure, or GCP) and data lake architectures. Experience in integrating Snowflake with third-party BI tools and APIs. Strong understanding of data warehousing concepts, data lakes, and dimensional modeling. Working knowledge of version control (Git), CI/CD practices, and Agile methodologies. Excellent problem-solving skills and ability to work in a collaborative environment. Preferred Qualifications: Snowflake Certification (SnowPro Core or Advanced). Experience with dbt (Data Build Tool) or similar modern data transformation frameworks. Exposure to Python or other scripting languages for data manipulation. Knowledge of data privacy and compliance standards (e.g., GDPR, HIPAA)