Data Engineer - Capgemini
Seattle, WA
About the Job
Data Engineer
FT Direct hiring with benefits
Hybrid role
Role and Responsibility:
- Strong
experience in building Azure Data engineering solutions using as Azure Data
factory, Databricks, Azure Data Lake and Azure SQL Database.
- Hands of
Experience in SSAS including Designing partitions, relationships, DAX query
Tuning
- Hands on
experience on automating Data Quality check for SSAS Cube vs sources
- Hands on
Experience on taking care multiple sources which flows in system at different
point of time throughout the day.
- Understanding
of Big Data platform like Hadoop , Spark internals.
- Developed
Spark applications using Pyspark and Spark-SQL for data
extraction, transformation, and aggregation from multiple file formats for
analyzing & transforming
- Used
Databrick notebooks to analyze and process the data from Data Lake into Azure
SQL database based on business requirements.
- Experience
with Spark (Databricks or Synapse) or Modern Data Architectures such as
Modern Data Warehouse and Data Mesh.
- Knowledge
of Microsoft Azure cloud or other similar public cloud platforms.
- Hands-on
experience from design through implementation of large-scale distributed data
systems, setting examples for good data engineering practices, Continuous
Integration/Continuous Deployment (CI/CD) and coding along the way.
- Possess
problem solving, technical, and data analysis skills.
- Good
communication skills and teamwork and comfort with agile software
development.
Email
resume to me at: harneet.sapra@sogeti.com
Thebenefits our employees enjoy:
+ Competitive Salary
+ 401(k) Savings Plan- Matched 150% up to 6%.
+ Medical, dental and vision benefits
+ 100% Company-paid mobile phone plan
+ 3 weeks Personal Time Off (PTO) and 7 Paid Holidays
Sogeti is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
FT Direct hiring with benefits
Hybrid role
Role and Responsibility:
- Strong
experience in building Azure Data engineering solutions using as Azure Data
factory, Databricks, Azure Data Lake and Azure SQL Database.
- Hands of
Experience in SSAS including Designing partitions, relationships, DAX query
Tuning
- Hands on
experience on automating Data Quality check for SSAS Cube vs sources
- Hands on
Experience on taking care multiple sources which flows in system at different
point of time throughout the day.
- Understanding
of Big Data platform like Hadoop , Spark internals.
- Developed
Spark applications using Pyspark and Spark-SQL for data
extraction, transformation, and aggregation from multiple file formats for
analyzing & transforming
- Used
Databrick notebooks to analyze and process the data from Data Lake into Azure
SQL database based on business requirements.
- Experience
with Spark (Databricks or Synapse) or Modern Data Architectures such as
Modern Data Warehouse and Data Mesh.
- Knowledge
of Microsoft Azure cloud or other similar public cloud platforms.
- Hands-on
experience from design through implementation of large-scale distributed data
systems, setting examples for good data engineering practices, Continuous
Integration/Continuous Deployment (CI/CD) and coding along the way.
- Possess
problem solving, technical, and data analysis skills.
- Good
communication skills and teamwork and comfort with agile software
development.
resume to me at: harneet.sapra@sogeti.com
Thebenefits our employees enjoy:
+ Competitive Salary
+ 401(k) Savings Plan- Matched 150% up to 6%.
+ Medical, dental and vision benefits
+ 100% Company-paid mobile phone plan
+ 3 weeks Personal Time Off (PTO) and 7 Paid Holidays
Sogeti is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
Source : Capgemini