Nagarro
Company Description
We're Nagarro. We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18 000+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! By this point in your career, it is not just about the tech you know or how well you can code. It is about what more you want to do with that knowledge. Can you help your teammates proceed in the right direction? Can you tackle the challenges our clients face while always looking to take our solutions one step further to succeed at an even higher level? Yes? You may be ready to join us.
Job Description We are seeking a highly skilled Data Engineer with strong expertise in Snowflake, ETL/ELT concepts, and dbt to design, build, and optimize scalable data pipelines. The ideal candidate will have advanced SQL skills, experience with cloud-based data platforms, and a strong understanding of data warehousing best practices.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Snowflake and dbt
Write and optimize advanced SQL queries for performance and reliability
Implement ETL/ELT processes to ingest and transform data from multiple sources
Develop Python scripts for automation, data processing, and API integrations
Build and manage data workflows using AWS services such as Glue, Lambda, S3, and CloudFormation
Design and maintain data warehouse models, schemas, and transformations
Collaborate with cross-functional teams to understand data requirements and deliver analytical solutions
Implement and maintain version control, CI/CD pipelines, and best development practices
Monitor, troubleshoot, and optimize data pipelines for performance and cost efficiency
Qualifications Required Skills
Strong hands-on experience with Snowflake
Advanced SQL proficiency
Strong understanding of ETL/ELT concepts and data pipelines
Hands-on experience with dbt
Solid knowledge of data warehousing concepts, including schema design and data modeling
Proficiency in Python for scripting and automation
Good to Have Skills
Experience with AWS services (Glue, Lambda, S3, CloudFormation)
Familiarity with Git and CI/CD practices
Understanding of APIs and CRUD operations
Exposure to cloud-native data architectures
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Job Description We are seeking a highly skilled Data Engineer with strong expertise in Snowflake, ETL/ELT concepts, and dbt to design, build, and optimize scalable data pipelines. The ideal candidate will have advanced SQL skills, experience with cloud-based data platforms, and a strong understanding of data warehousing best practices.
Key Responsibilities
Design, develop, and maintain scalable data pipelines using Snowflake and dbt
Write and optimize advanced SQL queries for performance and reliability
Implement ETL/ELT processes to ingest and transform data from multiple sources
Develop Python scripts for automation, data processing, and API integrations
Build and manage data workflows using AWS services such as Glue, Lambda, S3, and CloudFormation
Design and maintain data warehouse models, schemas, and transformations
Collaborate with cross-functional teams to understand data requirements and deliver analytical solutions
Implement and maintain version control, CI/CD pipelines, and best development practices
Monitor, troubleshoot, and optimize data pipelines for performance and cost efficiency
Qualifications Required Skills
Strong hands-on experience with Snowflake
Advanced SQL proficiency
Strong understanding of ETL/ELT concepts and data pipelines
Hands-on experience with dbt
Solid knowledge of data warehousing concepts, including schema design and data modeling
Proficiency in Python for scripting and automation
Good to Have Skills
Experience with AWS services (Glue, Lambda, S3, CloudFormation)
Familiarity with Git and CI/CD practices
Understanding of APIs and CRUD operations
Exposure to cloud-native data architectures
#J-18808-Ljbffr