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2 weeks ago
We are seeking an experienced data engineer to lead end-to-end data warehousing projects using Snowflake and dbt. The ideal candidate will have hands-on experience in AWS data services, Oracle, PL/SQL, and SQL, along with leadership experience in customer-facing roles for requirement gathering and solution design.
The role involves technical leadership & data engineering: designing and implementing scalable data models, ETL/ELT pipelines, and data architecture in Snowflake. Additionally, the candidate should develop and optimize dbt models, transformations, and data workflows for efficient analytics, work with AWS data services for data integration and migration, and ensure data governance, quality, and best practices in data engineering.
Key Responsibilities:- Lead data warehousing projects using Snowflake and dbt.
- 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 for data integration and migration.
- Ensure data governance, quality, and best practices in data engineering.
- 6-13 years of hands-on experience in Data Engineering, Data Warehousing, and Data Modeling.
- Expert-level proficiency in Snowflake and dbt.
- AWS Data Services, Oracle, PL/SQL, SQL, and database optimization.
- ETL/ELT pipelines & Data Integration. Data Architecture & Dimensional Modeling (Star Schema, Kimball, etc.).
- Experience in customer handling, requirement gathering, and solution design.
- Certification in Snowflake, dbt, or AWS Data Technologies.
- Experience with Python, PySpark, or other scripting languages.
- Knowledge of CI/CD pipelines for data workflows.
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