SQL Data Architect

Job Description

Strong experience working with retail Point-of-Sale (POS) Transaction Log (TLOG) files and mapping data to be used by other retail related business applications

Responsibilities

Define and document data ETL procedures, standards, and metrics to support customer analytics business rules. 
Establish data quality processes and compliance with data standards for data domains. 
Troubleshoot issues with data quality as identified by stakeholders. 
Perform activities to address data extraction, data validation, data cleansings, data harmonization, business logic, exception handling, and required data indication. 
Design and build a data inventory including field definitions, ontologies, list of values (LOVs), and mappings as requested by the stakeholder and defined by requirements. 
Understand critical data relationships and customer data domains. 
Collaborate with business process owners, data producers, and data consumers to get an understanding of current processes and systems that has a direct impact on the quality of the enterprise data. 
Work with business application engineers to define and maintain a customer data model and Analytics solutions.

Qualifications

Bachelor of Science degree and/or relevant work experience
7+ years of prior experience as a data analyst or architect
Strong experience working with retail point-of-sale (POS) transaction log (TLOG) files and mapping data to be used by other retail related business applications
Data Architect deep understanding of ETL Tools, Best Practice Processes (Enterprise ETL Tools, Self-Service, Data Preparation) 
Data Movement Tools (SSIS, Informatica, Talend, etc.) 
Proficient in SQL (SQL, Stored Procedures, Dynamic SQL, Joins, Aggregation, etc.) 
Experience with Data Structure Solutions (Big Data, RDBMS, NoSQL) 
Experience with a couple of Database Systems (Oracle, SQL Server, My SQL, Postgres, etc.) 
Skilled in one scripting language, such as R, Python, VBScript, Shell Script 
Understanding of Data Governance, Data Integrity, Master Data Management, Data Quality 
Design, Develop, and Deployment Best Practices 
Experience structuring and analyzing large quantities of data and information for statistical and analytical modeling 
Understanding of Business Intelligence Best Practices, Architectures, Tools, Methodologies, and Software 
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 
Experience with SDLC methodologies (Agile and Waterfall Development) 
Experience with Data Modeling