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Job Location | Chennai |
Education | Not Mentioned |
Salary | Not Disclosed |
Industry | IT - Software |
Functional Area | General / Other Software,DBA / Datawarehousing |
EmploymentType | Full-time |
Experience 5 8 YearsLocation Chennai / BangaloreRole Cloud ETL EngineerPrimary Skill SQL , Python , Hadoop, SparkSecondary Skill JavaJoining time less than 20 DaysJob DescriptionAs a Cloud ETL engineer you will be responsible for consolidating the many data sources the organization has into one central business accessible repository of data. The Cloud ETL Engineer s primary customer is internal analysts, scientists, and report writers that support the broader organization. Applicants to this position will ideally have spent the previous five or more years working with cloud data solutions and will be comfortable not only lifting and shifting data but structured data repositories as well. As a modern ETL team engineers are organized into teams following Agile software development practice. We use Git repos and CI/CD deployment constructs. Because of the nature of data we need engineers that understand data security, ownership, classification, access management and should have previously worked with protected health information, personally identifiable information, as well as material non-public information. Client is also subject to GLBA, HIPAA, CCPA and many more legislative regulations.Candidates should have 5+ years of experience in many of the following knowledge sets:Broad SQL data interrogation knowledge and query optimization on the following platformsMicrosoft SQL Server | Oracle | Other ANSI standard databasesProficiency with cloud data streaming tools including but not limited to Airflow | DBT | KakfaProficient in the following languages Python | SQL | C# or JavaFamiliarity with data warehousing concepts Kimbal | Data Vault | Inmon
Keyskills :
data vaultmaster data managementdata streamingmachine learningoptimization strategiesdata securitydata managementetlsql serverdata warehousingdata solutionssqlmaster datadata governance