Job Title: Data Engineer - Data Platforms
Job Description
We are seeking a Data Engineer with 8+ years of experience designing and building cloud-native data platforms. The ideal candidate will have strong expertise in Snowflake, advanced SQL, data Modeling, Python, and cloud technologies to develop scalable ELT pipelines and optimize data processing for enterprise analytics.
Key Responsibilities
Key Responsibilities: Data Pipelines: Build, maintain, and optimize robust ELT pipelines to process large volumes of structured and semi-structured data.
Snowflake Architecture: Configure and manage virtual warehouses, stages, Snowpipe, streams, and tasks.
SQL Development: Write clean, highly optimized SQL queries, stored procedures, and User-Defined Functions (UDFs).
Performance Tuning: Monitor query performance and apply tuning techniques like clustering keys, materialized views, and result caching.
Security & Governance: Implement Role-Based Access Control (RBAC), row/column-level security, and data masking.
Integration & Transformation: Work with transformation tools like dbt, or use Snowpark with Python/Java for advanced analytics.
Essential Qualifications Experience: 4+ to 5+ years of hands-on experience building cloud-native data platforms, with at least 3+ years specifically in Snowflake.
Technical Skills: Advanced SQL, Data Modeling (Star/Snowflake schema), and scripting (Python, Bash).
Tools: Proficiency with cloud environments (AWS, Azure, or Google Cloud Platform) and ELT/ETL integration tools.
Soft Skills: Strong analytical problem-solving, capability to translate business requirements into technical data structures, and Agile/Scrum team collaboration.
Required skills: Advance SQL, Data Modeling (Star/Snowflake schema), and scripting (Python, Bash).
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