Capgemini
Insurance
FBSDataEngineer
Neural analysis suggests this role is
optimal for Mid candidates.
“FBS Data Engineer at Capgemini. Skills: Data Engineering, SQL, Data Modeling, ETL/ELT. Analyze data from multiple source systems. Design Data Marts based on business requirements”
Industry & Context.
What They're Looking For.
Must Have
5-7 years relevant experience, Advanced SQL, Intermediate DBT, Intermediate Python, Intermediate GitHub, Advanced Snowflake, Intermediate CI/CD practices, Intermediate ETL/ELT pipeline design
Nice to Have
Hands-on AWS experience, Hands-on Azure experience
What You'll Do.
Analyze data from multiple source systems
Design Data Marts based on business requirements
Model Data Marts based on business requirements
Create technical documents
Understand design requirements
Understand existing business processes
Lead design of data products
Lead development of data products
Lead implementation of data products
Support Specialty data vault
Use Specialty data vault
Write complex SQL statements
Load data mart tables using DBT
How You'll Work.
Team & Collaboration
Partnership with business partners; Partnership with data scientists
Communication Scope
Communication skills
Full Job Description
A data engineer role in the Specialty Data team should be able to analyze data from multiple source system and design/model Data Marts based on business requirements. Therefore, strong data analytics and technical skills are a must. He or She should be able to create data models, STTMs and other technical documents. The Engineer should have strong communication skills and the ability to understand design requirement and existing business processes to lead in the design, development, and implementation of data products in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Intermediate expertise in Data Vault 2.0 Modeling to be able to support and use the Specialty data vault. 2) Advance Expertise in SQL. The Engineer will be writing complex SQL statements. 3) Intermediate expertise in DBT, Phyton and GitHub development. The Engineer should be able to use DBT as an ELT tool to load the data mart tables. 4) Advance expertise in Snowflake database. 5) Some knowledge of Mainframe, Mainframe SAS and Distributed DB2. Mainframe is a source system of the mart. 6) Some knowledge on the Fivetran tool. Fivetran is used as an Orchestrating tool of the DBT code. 7) Hands-on experience with multiple cloud platforms including AWS and Azure is preferred. 8) Informatica development skills. 9) Good understanding of Medallion Data Architecture **Total Experience- 05 to 07 years** **Relevant Experience 05 to 07 years** **Requirements** **Other Critical Skills** SQL - Advanced Critical Thinking - Intermediate Ownership - Intermediate Experienced in CI/CD practices - Intermediate Designing scalable ETL/ELT pipelines - Intermediate **Software / Tool Skills** Python - Intermediate (4-6 Years) DBT - Advanced (7+ Years) Airflow - Intermediate (4-6 Years) GitHub Desktop - Intermediate (4-6 Years) Informatica - Intermediate (4-6 Years) Microsoft Visual Studio - Intermediate (4-6 Years) DB2 connect personal edition - Intermed
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