ETL/Oracle - Data Warehouse Lead
This is not a corp to corp position.
Need EAD/GC/Citizen. H1 transfer can be considered.
Duration: 6 months
General Requirements:
In-depth theoretical understanding and practical expertise with regards to data warehousing architecture and methodology
Min. 8 years of hands-on data warehousing expertise covering all aspects of software project life-cycle, i.e. business and data modeling, data analysis, system design, development, etc.
Experience in working with the large-scale (100+ entities) relational data models
Must have prior experience leading successful data warehousing implementations as well as a broad background and experience with IT application development.
Thorough understanding of relational and dimensional data modeling techniques
Min. 8 years of hands-on expertise with Oracle databases, especially 9i/10g
Strong knowledge of SQL, PL/SQL, performance tuning techniques for working with the large volume tables
Familiarity with data modeling tools such as ERWIN (3.5 and 4.1)
Familiarity with various process modeling techniques (activity hierarchy diagrams, data flow diagrams, sequence diagrams, workflow diagrams, system interface diagrams)
Excellent communication and facilitation skills
The candidate must demonstrate knowledge of data warehouse implementation process, from business requirements through logical modeling, physical database design, data sourcing and data transformation, data loading, SQL, end-user tools, database and SQL performance tuning.
Identify business and functional requirements, and actively participate in the requirements, design and build phases; delivering high quality deliverables
Provide overall support to ensure the successful planning, design, testing and implementation of Business Intelligence applications.
Team work and collaborate with IT professionals to determine if solutions currently exist (internally or externally) or whether new solutions are feasible to meet business requirements and to ensure consistency among related workflows.
Masters degree, majoring in Engineering/Computer Science/Information Systems/Finance, specialized training or equivalent work experience with a minimum of > 8 years relevant technical and business work experience
At least 8 years of experience in defining and implementing technology solutions for large scale enterprise application systems, preferably from a major financial institution, asset manager, or Wall Street bank
At least 8 years of experience in analysis, design, development, and deployment of large scale enterprise application systems
Extensive experience in documenting technical design, developing functional specifications, and defining data models (logical and physical)
Good knowledge and experience with Financial industries complement a high level proficiency in DBMS Technologies, Data Extraction and Integration Strategies (ETL and ELT), and Data Warehouse Modeling using traditional and hybrid Methodologies.
>6 years Oracle PL/SQL development experience
>6 years Unix scripting
>3 implementations of large multi subject data warehouses at Fortune 500 companies
Familiarity with Cognos a plus
Familiarity with Sybase development environment
The Data Warehouse Lead is responsible for developing and managing technical activities related to migrating Summit DR from Sybase to Oracle. The Technical lead in consultation with project manager - develops and executes project schedules, supervising personnel and communicating policies, procedures, and goals to team members.
This individual will carry out the following activities for Summit DR migration project:
Design logical and physical data models in collaboration with Data Modeler.
Design and development of required various Oracle database objects.
Analysis of documented user requirements.
Develop schedule estimations for migrating Summit DR from Sybase to Oracle
Develop working prototypes of conceptual solutions.
Design, Develop and maintain Unix scripts for automating Data Load process
Design, Develop and maintain ETL processes for migrating data from Sybase to Oracle.
Trouble-shoot data load/database refresh issues and errors.
Validate data warehouse data back to the source system.
In-depth theoretical understanding and practical expertise with regards to data warehousing architecture and methodology
Min. 8 years of hands-on data warehousing expertise covering all aspects of software project life-cycle, i.e. business and data modeling, data analysis, system design, development, etc.
Experience in working with the large-scale (100+ entities) relational data models
Must have prior experience leading successful data warehousing implementations as well as a broad background and experience with IT application development.
Thorough understanding of relational and dimensional data modeling techniques
Min. 8 years of hands-on expertise with Oracle databases, especially 9i/10g
Strong knowledge of SQL, PL/SQL, performance tuning techniques for working with the large volume tables
Familiarity with data modeling tools such as ERWIN (3.5 and 4.1)
Familiarity with various process modeling techniques (activity hierarchy diagrams, data flow diagrams, sequence diagrams, workflow diagrams, system interface diagrams)
Excellent communication and facilitation skills
The candidate must demonstrate knowledge of data warehouse implementation process, from business requirements through logical modeling, physical database design, data sourcing and data transformation, data loading, SQL, end-user tools, database and SQL performance tuning.
Identify business and functional requirements, and actively participate in the requirements, design and build phases; delivering high quality deliverables
Provide overall support to ensure the successful planning, design, testing and implementation of Business Intelligence applications.
Team work and collaborate with IT professionals to determine if solutions currently exist (internally or externally) or whether new solutions are feasible to meet business requirements and to ensure consistency among related workflows.
Masters degree, majoring in Engineering/Computer Science/Information Systems/Finance, specialized training or equivalent work experience with a minimum of > 8 years relevant technical and business work experience
At least 8 years of experience in defining and implementing technology solutions for large scale enterprise application systems, preferably from a major financial institution, asset manager, or Wall Street bank
At least 8 years of experience in analysis, design, development, and deployment of large scale enterprise application systems
Extensive experience in documenting technical design, developing functional specifications, and defining data models (logical and physical)
Good knowledge and experience with Financial industries complement a high level proficiency in DBMS Technologies, Data Extraction and Integration Strategies (ETL and ELT), and Data Warehouse Modeling using traditional and hybrid Methodologies.
>6 years Oracle PL/SQL development experience
>6 years Unix scripting
>3 implementations of large multi subject data warehouses at Fortune 500 companies
Familiarity with Cognos a plus
Familiarity with Sybase development environment
The Data Warehouse Lead is responsible for developing and managing technical activities related to migrating Summit DR from Sybase to Oracle. The Technical lead in consultation with project manager - develops and executes project schedules, supervising personnel and communicating policies, procedures, and goals to team members.
This individual will carry out the following activities for Summit DR migration project:
Design logical and physical data models in collaboration with Data Modeler.
Design and development of required various Oracle database objects.
Analysis of documented user requirements.
Develop schedule estimations for migrating Summit DR from Sybase to Oracle
Develop working prototypes of conceptual solutions.
Design, Develop and maintain Unix scripts for automating Data Load process
Design, Develop and maintain ETL processes for migrating data from Sybase to Oracle.
Trouble-shoot data load/database refresh issues and errors.
Validate data warehouse data back to the source system.
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