Snowflake Data Engineer
Indexed description
Roles & Responsibilities
Team Leadership & Mentorship:
- Guide and mentor junior data engineers in Snowflake, dbt, and modern data stack best practices
- Ensure adherence to data security, compliance, and scalability principles
- 6-13 years of hands-on experience in Data Engineering, Data Warehousing, and Data Modeling
- Expert-level proficiency in Snowflake and dbt (data build tool) - Mandatory
- Strong expertise in:
- AWS Data Services (Aurora, RDS, DMS, DynamoDB)
- Oracle, PL/SQL, SQL, and database optimization
- ETL/ELT pipelines & Data Integration
- Data Architecture & Dimensional Modeling (Star Schema, Kimball, etc.)
Technical Leadership & Data Engineering
- Lead end-to-end data warehousing projects using Snowflake, DataStage and dbt (mandatory skills)
- Design and implement scalable data models, ETL/ELT pipelines, and data architecture in Snowflake
- Develop and optimize dbt models, transformations, and data workflows for efficient analytics
- Work with AWS data services - Aurora, RDS, DMS, DynamoDB - for data integration and migration
- Optimize SQL, PL/SQL queries and database performance (Oracle, PostgreSQL, etc.)
- Implement CDC (Change Data Capture) and real-time data processing solutions
- Ensure data governance, quality, and best practices in data engineering
- Collaborate with stakeholders to gather, analyze, and document business requirements
- Handle Change Requests (CRs) and provide technical solutions aligned with business needs
- Act as a bridge between business teams and technical teams for data-driven decision-making
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