Analytics Information Architect

Company: U.S. Venture
Location: Appleton , Wisconsin, United States
Type: Full-time
Posted: 12.OCT.2018


Work location will be: 425 BETTER WAY Make your mark with us! To learn more about working at U.S. Venture, watch this video: Life at U.S....


Work location will be:


Make your mark with us!

To learn more about working at U.S. Venture, watch this video: Life at U.S. Venture


The Analytics Information Architect would be the custodian of enterprise data model, with a focus on master data management (MDM) and predictive analytics in a big data environment, to enable insight and analytics capabilities, represented by cloud computing, open-source programming, and analytics-based decision making.

The role requires close partnership and collaboration with the organization's Data Resource Management Team, Data Scientists, Data Analysts, and Business Intelligence Analysts to create a mature data management and advanced analytics ecosystem.


* Forward looking: Be the strategist and designer for data strategy, infrastructure, and workflow processes: connecting with ERP and Data warehouses, focus on BI and predictive / prescriptive analytics uses so that we proactively create a road map and eco-system for future growth and monetization of data/info (internally and potentially externally). Implications of open source programming, cloud computing, IoT, Blockchain, and other technological changes/trends.

* Realistic: Have a solid footing on past data practices and current landscape (pros and cons, limitations and opportunities). Data governance, process change, organizational influence, etc.

* Create an enterprise data framework and data model covering Customer, Product, Customer Interaction & Transaction, Inventory, Operations and Supply Chain / Warehouse Management, Web and Mobile Analytics subject areas.

* Translate user requirements and business use cases to conceptual, logical, and physical data models and workflow processes.

* Act as bridge and translator between business data SMEs (subject matter experts) and technical data SMEs and guide requirements conversations through a structured approach that builds business confidence in the process.

* Translate a business glossary into logical and physical data models, and assist / support engineers in their development / testing / implementation effort.

* Create a tiered enterprise data management architecture to support analytics, using a combination of relational, dimensional and flat data models, depending on business context, type of data, and use cases.

* Identify appropriate sources for the data science team's data needs, create the necessary data mapping and transformation rules (with a focus on business objective and processes) and assist the data engineering team in staging / curating the data for advanced analytics

* Facilitate the data scientists, data analysts, and business intelligence analysts in using master data and analytic data by walking them through the framework, roadmap, model structure, and workflow using business scenarios familiar to them.

* Identify and recommend the appropriate data management toolset for managing master data and predictive data management.

* Create a framework to house external data from third-party vendors and partners by mapping them to the enterprise business glossary and enterprise data model.

* Maintain cross-referenced metadata on data sources, interfaces and systems of record and systems of reference.

* Advise the data resource management team on data quality rules and identify appropriate mechanisms to execute and update results of data quality checks.

* Create a framework for reusable data feeds (such as Web Services and batch feeds) to external partners and vendors for short-term and long-term business projects and programs.

* Recommend and bring data management best practices to combine disparate data and analytics requirements and projects under a consolidate data management umbrella that spans the organization.


* Bachelor's Degree in relevant academic discipline(s), such as information technology, management information systems, engineering, science, etc.; or equivalent work experience

* Minimum 5 years' experience as a Data Modeler and Data Architect, in an integrated business and IT collaborative environment.

* Combination of strategic thinking and detail orientation.

* Demonstrated ability to balance being inquisitive, curious, continuously learning, and realistic vs. visionary, technology savvy, and business orientation.

* Strong skills on business partnership relationship building and communication (in meetings and in writing).

* Strong hands-on documentation experience and ability to communicate complex topics in simpler terms.

* Strong understanding of the retail domain and business processes.

* Specific experience in metadata and master data management, with an integrated focus on customer and product.

* Expert to advanced proficiency in data modeling for relational, dimensional and big data platforms.

* Experience with at least one end-to-end big data implementation on the Hadoop platform.

* Knowledge and exposure to industry standard models (for example, Microsoft SQL Server, Oracle, IBM, etc.).



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