Project Manager

Overview

On Site
USD60 - USD64
Contract - W2

Skills

Project Manager

Job Details

job summary:

Manager, Data Engineering



Job Description Summary




  • Enable Marketplace item setup specifications, from a global spec alignment standpoint, in collaboration with the various markets


  • Engage with project teams on Strategic Initiative spec creation and management


  • Perform item data analysis to drive improved attribute coverage and quality


  • Write requirements and author one-pagers for EII project prioritization as needed


  • Utilize the Governance process to align attributes and technology across domains and markets


  • Provide feedback on system functionalities and continuous improvement opportunities


  • Provide feedback on spec data models and attribution to surface continuous improvement opportunities



Job Description



Data Strategy Requires knowledge of: Understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.



Data Source Identification Requires knowledge of: Functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores; Data Quality; Existing business systems and processes, including the key drivers and measures of success. To support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.



Data Transformation and Integration Requires knowledge of: Internal and external data sources including how they are collected, where and how they are stored, and interrelationships, both within and external to the organization; Develops knowledge of current data science and analytics trends.



Tech. Problem Formulation Requires knowledge of: Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.



Understanding Business Context Requires knowledge of: Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, project management, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work.



Data Governance Requires knowledge of: Data value chains; Data processes and practices; Regulatory and ethical requirements around data; Data modeling, storage, integration, and warehousing; Data value chains (identification, ingestion, processing, storage, analysis, and utilization); Data quality framework and metrics; Regulatory and ethical requirements around data privacy, security, storage, retention, and documentation; Business implications on data usage; Data Strategy; Enterprise regulatory and ethical policies and strategies. To establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices, or guidelines.





location: Bentonville, Arkansas

job type: Contract

salary: $60 - 64 per hour

work hours: 8am to 5pm

education: Bachelors



responsibilities:

Manager, Data Engineering



Job Description Summary




  • Enable Marketplace item setup specifications, from a global spec alignment standpoint, in collaboration with the various markets


  • Engage with project teams on Strategic Initiative spec creation and management


  • Perform item data analysis to drive improved attribute coverage and quality


  • Write requirements and author one-pagers for EII project prioritization as needed


  • Utilize the Governance process to align attributes and technology across domains and markets


  • Provide feedback on system functionalities and continuous improvement opportunities


  • Provide feedback on spec data models and attribution to surface continuous improvement opportunities



Job Description



Data Strategy Requires knowledge of: Understanding of business value and relevance of data and data enabled insights / decisions; Appropriate application and understanding of data ecosystem including Data Management, Data Quality Standards and Data Governance, Accessibility, Storage and Scalability etc; Understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.



Data Source Identification Requires knowledge of: Functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores; Data Quality; Existing business systems and processes, including the key drivers and measures of success. To support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.



Data Transformation and Integration Requires knowledge of: Internal and external data sources including how they are collected, where and how they are stored, and interrelationships, both within and external to the organization; Develops knowledge of current data science and analytics trends.



Tech. Problem Formulation Requires knowledge of: Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.



Understanding Business Context Requires knowledge of: Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, project management, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work.



Data Governance Requires knowledge of: Data value chains; Data processes and practices; Regulatory and ethical requirements around data; Data modeling, storage, integration, and warehousing; Data value chains (identification, ingestion, processing, storage, analysis, and utilization); Data quality framework and metrics; Regulatory and ethical requirements around data privacy, security, storage, retention, and documentation; Business implications on data usage; Data Strategy; Enterprise regulatory and ethical policies and strategies. To establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices, or guidelines.





qualifications:

Manager, Data Engineering



Job Description Summary




  • Enable Marketplace item setup specifications, from a global spec alignment standpoint, in collaboration with the various markets


  • Engage with project teams on Strategic Initiative spec creation and management


  • Perform item data analysis to drive improved attribute coverage and quality


  • Wri


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