GEP is a diverse, creative team of people passionate about procurement. We invest ourselves entirely in our client’s success, creating strong collaborative relationships that deliver extraordinary value year after year. Our clients include market global leaders with far-flung international operations, Fortune 500 and Global 2000 enterprises, leading government and public institutions.
We deliver practical, effective services and software that enable procurement leaders to maximise their impact on business operations, strategy and financial performance. That’s just some of the things that we do in our quest to build a beautiful company, enjoy the journey and make a difference. GEP is a place where individuality is prized, and talent respected. We’re focused on what is real and effective. GEP is where good ideas and great people are recognized, results matter, and ability and hard work drive achievements. We’re a learning organization, actively looking for people to help shape, grow and continually improve us.
Are you one of us?
GEP is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, ethnicity, color, national origin, religion, sex, disability status, or any other characteristics protected by law. We are committed to hiring and valuing a global diverse work team.
For more information please visit us on GEP.com or check us out on LinkedIn.com.
Exercise strong decision-making skills in terms of data analysis and architecting large data infrastructures
Work with Machine the learning team to utilize pattern recognition, text mining, clustering, and AI
Review functional and technical requirements, raising potential issues and participating actively in design discussions
Collaborate with both technical and business stakeholders to understand data platform requirements
Understand and contribute to future state guidelines and vision
Create and document future state architectural options to address specific issues or initiatives
Working as a member of a design, build and test agile team, continuously releasing new updates
Maintain in-depth and current knowledge of Cloud Data Services (Azure / AWS), their main components, tradeoffs, pros and cons for each, knowledge of when to use each, and how they can be optimally combined to create data patterns and frameworks
Perform requirement analysis, data profiling, effort estimation for database and data warehouse design and development
Provide thought leadership around big data ecosystem and data warehouse design by leveraging past experiences
Provide guidance on the creation and best practices around Data Governance, Data Stewardship and overall Data Quality initiatives and processes, as part of the overall data effort
Develop and maintain conceptual, logical, and physical big data platform, database and data warehouse architectures
Collaboratively support the development and deployment of architectures supporting the enterprise big-data and data warehouse environments
Collaborate with the Enterprise Architect and client IT team as warranted to establish and implement strategic initiatives
Guides team members on the development of Spark programs to ingest/process data
Bachelor’s degree or higher in Computer Science or a related field
Expert knowledge in Azure HDInsight, Azure Data Lake, Spark, Hive, MongoDB and how to implement microservices based architecture to establish complete data lifecycle
Ability to design Hadoop ecosystem and data warehousing solutions that can take large volumes of structured and unstructured data and rapidly generate meaningful reports and/or support ongoing analytical needs
Thorough knowledge of database design and tuning with standard tools
Experience implementing operational and dimensional logical and physical design for Data Marts, Data Warehouse and Business intelligence solutions
Experience architecting and designing solutions that leverage Master Data Management (MDM), Reference Data Management, Integration solutions, Operational Data Stores (ODS), and Analytic Data Stores (ADS)
Experience in identifying and documenting data integration issues, challenges such as duplicate data, non-conformed data, and unclean data including both internal and external data sources
Experience in identifying, analyzing and translating business requirements into conceptual, logical and physical data models in complex, multi-application environments
Excellent data analysis skills using SQL.
Experience in creating, reviewing and presenting Source Systems Analysis and Source To Target mapping across Staging, Integration and Presentation layers
Experience in Data analysis/profiling and reverse engineering of data
Requisition ID: 2022-25581
External Company URL: https://careers.gep.com/
Street: Building No. 3
What You Will Do (Text Only): – Exercise strong decision-making skills in terms of data analysis and architecting large data infrastructures
– Work with Machine the learning team to utilize pattern recognition, text mining, clustering, and AI
– Review functional and technical requirements, raising potential issues and participating actively in design discussions
– Collaborate with both technical and business stakeholders to understand data platform requirements
– Understand and contribute to future state guidelines and vision
– Create and document future state architectural options to address specific issues or initiatives
– Working as a member of a design, build and test agile team, continuously releasing new updates
– Maintain in-depth and current knowledge of Cloud Data Services (Azure / AWS), their main components, tradeoffs, pros and cons for each, knowledge of when to use each, and how they can be optimally combined to create data patterns and frameworks
– Perform requirement analysis, data profiling, effort estimation for database and data warehouse design and development
– Provide thought leadership around big data ecosystem and data warehouse design by leveraging past experiences
– Provide guidance on the creation and best practices around Data Governance, Data Stewardship and overall Data Quality initiatives and processes, as part of the overall data effort
– Develop and maintain conceptual, logical, and physical big data platform, database and data warehouse architectures
– Collaboratively support the development and deployment of architectures supporting the enterprise big-data and data warehouse environments
– Collaborate with the Enterprise Architect and client IT team as warranted to establish and implement strategic initiatives
Guides team members on the development of Spark programs to ingest/process data
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