Database Architect

USC/GC due to legal or govt. contract requirement. W2/Own corp. Job description: The core skillset needed Snowflake, informatica for ETL, Erwin for data modeling and Oracle Database. They must have enterprise experience doing 3rd party integrations. Job Description: Skills: (All Skillsets at least 5-7 years) • Knowledge of SQL language and cloud-based technologies (SQL – 10 years) • Data warehousing concepts, data modeling, metadata management • Data lakes, multi-dimensional models, data dictionaries • Performance tuning and setting up resource monitors • Snowflake modeling – roles, databases, schemas • SQL performance measuring, query tuning, and database tuning • ETL tools with cloud-driven skills • Ability to build analytical solutions and models • Root cause analysis of models with solutions • Hadoop, Spark, and other warehousing tools • Managing sets of XML, JSON, and CSV from disparate sources • SQL-based databases like Oracle SQL Server, Teradata, etc. • Snowflake warehousing, architecture, processing, administration • Data ingestion into Snowflake • Enterprise-level technical exposure to Snowflake applications Responsibilities: • Create, test, and implement enterprise-level apps with Snowflake • Design and implement features for identity and access management • Create authorization frameworks for better access control • Implement novel query optimization, major security competencies with encryption • Solve performance issues and scalability issues in the system • Transaction management with distributed data processing algorithms • Possess ownership right from start to finish • Build, monitor, and optimize ETL and ELT processes with data models • Migrate solutions from on-premises setup to cloud-based platforms • Understand and implement the latest delivery approaches based on data architecture • Project documentation and tracking based on understanding user requirements • Perform data integration with third-party tools including architecting, designing, coding, and testing phases • Manage documentation of data models, architecture, and maintenance processes • Continually review and audit data models for enhancement • Maintenance of ideal data pipeline based on ETL tools • Coordination with BI experts and analysts for customized data models and integration • Code updates, new code development, and reverse engineering • Performance tuning, user acceptance training, application support • Maintain confidentiality of data • Risk assessment, management, and mitigation plans • Regular engagement with teams for status reporting and routine activities • Migration activities from one database to another or on-premises to cloud