AWS DataEngineer required
Budget: ₹12,500 – ₹37,500 INR
A business-centric, data-oriented, and analytical mindset.
Comprehensive knowledge of data science concepts and disciplines.
Knowledge of enterprise information management processes and methodologies.
Skills in database design, data security, and data lifecycle management (i.e., gathering, cleansing, publishing, archiving, back-up and recovery, and purging) for large enterprise systems.
Familiarity with master data, metadata, reference data, data warehousing, database structure, business intelligence principles and processes, and technical architecture.
Knowledge of database management systems, metadata management tools, cloud storage, and associated security considerations.
. Combinations of experience and education will be considered on a case-by-case basis.
Experience in data warehousing and governance.
Practical experience in enabling data usability, availability, and efficiency.
Experience in data management, quality, metadata management, and modeling.
Knowledge of database systems: MS SQL Server, Oracle, or another commercial RDBMS required, Snowflake, or other non-relational database desired.
Knowledge of SQL.
Experience with scripting languages, especially Python, and PowerShell.
Comprehensive knowledge of data science concepts and disciplines.
Knowledge of enterprise information management processes and methodologies.
Skills in database design, data security, and data lifecycle management (i.e., gathering, cleansing, publishing, archiving, back-up and recovery, and purging) for large enterprise systems.
Familiarity with master data, metadata, reference data, data warehousing, database structure, business intelligence principles and processes, and technical architecture.
Knowledge of database management systems, metadata management tools, cloud storage, and associated security considerations.
. Combinations of experience and education will be considered on a case-by-case basis.
Experience in data warehousing and governance.
Practical experience in enabling data usability, availability, and efficiency.
Experience in data management, quality, metadata management, and modeling.
Knowledge of database systems: MS SQL Server, Oracle, or another commercial RDBMS required, Snowflake, or other non-relational database desired.
Knowledge of SQL.
Experience with scripting languages, especially Python, and PowerShell.