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Business Intelligence Architect/Data Scientist  
Atlanta, GA 75%+
Sponsorship not available.

We seek to fill a BI Architect position that requires 10+ years of prior experience as a BI Architect. The position is a consultative technical position working with large enterprise customers who will implement end-to-end data management solutions on multiple BI platforms such as Azure Data Warehouse services (Azure Synapse Analytics, Databricks, Pureview, Data Factory, Azure Analysis Services), AWS services (Redshift, Glue, Kafka, Kinesis, Data Pipelin, RDS), Cloudera, DataBricks, Teredata, Snowflake, Alteryx, Talend, SSIS, Informatica, Power BI, and Tableau to name a few.

We are looking for a candidate who can interact directly with our clients to consult, solicit business rules, design, and build solutions to address the client’s business intelligence and data management challenges. The BI Architect position may be required to create, modify, and maintain data entities based on customer requirements and initiatives. This position requires working well in teams as well as independently on projects. As a customer-facing position, excellent communication skills - oral and written - are essential to success, including effective management of customer expectations and needs, proactive anticipation of technical challenges, and a detailed yet personable consultative approach that builds client trust and well-being.

Design, development, and implementation of end-to-end data management solutions will require, amongst other things, expertise overseeing data sourcing, architecture, integration, data storage, data transfer, and visualization such as Power BI/Tableau dashboard development. The candidate must display advanced data query and manipulation skills – data modeling, data blending, and data integration. Candidates must demonstrate proficiency in making useful inferences and driving improvement actions from large data sets that are messy and not easily understood.

There may be up to 75% travel required, and daily work activities are managed within a virtual environment supported by the ability to telecommute.
Design, development, and implementation of end-to-end data management solutions will require, amongst other things, expertise overseeing and leading Business Intelligence projects with advanced skills in data query and manipulation – data modeling, data blending, and data integration. Candidates must demonstrate proficiency in making useful inferences and driving improvement actions from large data sets that are messy and not easily understood.
•    Experience leading a team of business intelligence resources throughout an entire project lifecycle
•    Experience leading the definition and documentation of all business intelligence policies and procedures, standards, design, and metrics to support customer analytic business rules
•    Cloud Platform (Azure, AWS, Snowflake, etc.)
•    Statistical analysis tools (MiniTab, SAS, SPSS, etc.…)
•    Data Visualization Tools (Power BI, Tableau, Qlik, etc.)
•    Proficient SQL (SQL, Stored Procedures, Dynamic SQL, Joins, Aggregation, etc.)
•    Experience with Data Structure Solutions (Big Data, RDBMS, NoSQL)
•    Experience with Databases (Oracle, SQL Server, My SQL, Postgress, etc.)
•    Skilled in one or more scripting languages, such as R, Ruby, Javascript, Python, VBScript, Shell Script
•    Deep understanding of data governance, data integrity, master data management, data quality design, development, and deployment best practices.
•    Deep understanding of technology-based business processes, including related business models, technical components, modern software development processes, i.e., Agile Scrum, etc.
•    Experience structuring and analyzing large quantities of data and information for statistical and analytical modeling
•    Deep understanding of BI best practices, architectures, tools, methodologies, and Software
•    Exposed to ETL tools, best practice processes - enterprise ETL tools, self-service, data preparation
•    Good strong oral, written communication, and leadership skills
•    Proven ability to partner with client stakeholders from various parts of an organization
•    Ability to handle multiple tasks and workstreams in a fast-paced environment
•    SDLC methodologies (Waterfall and Agile Development)
•    Proficiency with data modeling and experience using data modeling tools like ERwin, Visio, ER/Studio, Oracle Designer
•    Proficiency in predictive analytics, AI, and ML
•    Effectively communicate with internal and external customers to capture current data management requirements and objectives from different stakeholders that define their needs.
 SQLTableauETL ToolsPythonRDBMSStatistical Analysis SoftwareData ModelingAzure SynapseAWS
Bachelor’s Degree 5 - 10 Years
AdaptabilityAmbitionAnalytical ThinkingBuilding RelationshipsBusiness Systems ThinkingCommunicationConflict ResolutionCustomer OrientationDecision MakingDetail-OrientedEvaluating AlternativesFlexibilityFollow-up and ControlInitiativeInterpersonal SkillsInnovationIntegrityIntroducing ChangeListening
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When you bring additional fields into a conversion, Quickbase often finds inconsistencies. For example, say you're converting your Companies column into its own table. One company, Acme Corporation, has offices in New York, Dallas and Portland. So, when you add the City column to the conversion, Quickbase finds three different locations for Acme. A single value in the column you're converting can only match one value in any additional field. Quickbase needs you to clean up the extra cities before it can create your new table. To do so, you have one of two choices:

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  • If the dissimilar entries are mistakes (say Acme only has one office in New York and the other locations are data-entry errors) go back into your table and correct the inconsistencies—in this case, changing all locations to New York. Then try the conversion again.

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