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Cloud Data Engineer
Adesso
Cloud Data Engineer
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Cloud Data Engineer

at Adesso

Agency job
3 - 6 yrs
₹4L - ₹24L / yr
Kochi (Cochin), Chennai, Pune
Skills
Data engineering
skill iconAmazon Web Services (AWS)
Windows Azure
Snowflake
Data Transformation Tool (DBT)
SQL
Datawarehousing
Data Lake

We are seeking a skilled Cloud Data Engineer who has experience with cloud data platforms like AWS or Azure and especially Snowflake and dbt to join our dynamic team. As a consultant, you will be responsible for developing new data platforms and create the data processes. You will collaborate with cross-functional teams to design, develop, and deploy high-quality frontend solutions. 

Responsibilities:

Customer consulting: You develop data-driven products in the Snowflake Cloud and connect data & analytics with specialist departments. You develop ELT processes using dbt (data build tool) 

Specifying requirements: You develop concrete requirements for future-proof cloud data architectures.

Develop data routes: You design scalable and powerful data management processes.

Analyze data: You derive sound findings from data sets and present them in an understandable way.

Requirements:

Requirements management and project experience: You successfully implement cloud-based data & analytics projects.

Data architectures: You are proficient in DWH/data lake concepts and modeling with Data Vault 2.0.

Cloud expertise: You have extensive knowledge of Snowflake, dbt and other cloud technologies (e.g. MS Azure, AWS, GCP).

SQL know-how: You have a sound and solid knowledge of SQL.

Data management: You are familiar with topics such as master data management and data quality.

Bachelor's degree in computer science, or a related field.

Strong communication and collaboration abilities to work effectively in a team environment.

 

Skills & Requirements

Cloud Data Engineering, AWS, Azure, Snowflake, dbt, ELT processes, Data-driven consulting, Cloud data architectures, Scalable data management, Data analysis, Requirements management, Data warehousing, Data lake, Data Vault 2.0, SQL, Master data management, Data quality, GCP, Strong communication, Collaboration.

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