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VDOT Data Analyst/Cloud ETL Developer

1 month ago

Richmond, United States Argyllinfotech Full time
Job DescriptionJob DescriptionJob Summary:

1. The position is for a Master Data Analyst to work as a part of the Enterprise Data Asset team at the Virginia Department of Transportation (VDOT) Information Technology Division (ITD).

2. The role involves analyzing datasets for a cloud-based data management platform, developing data requirements, user stories, acceptance criteria, and testing strategies.

3. The Data Analyst is also required to develop ETL to extract business and spatial data and load it into a data warehousing environment.

4. The role requires deep knowledge of coding languages such as Python, Java, XML, SQL, and warehousing architecture techniques such as MOLAP, ROLAP, ODS, DM, and EDW.

5. The position requires working closely with various teams to understand the company's data storage needs and develop data warehousing options.

6. The Data Analyst will be responsible for managing multiple projects, maintaining flexibility and productivity in a fast-paced environment.

7. The role also involves working with the Project team members and business stakeholders to understand business processes and pain points, eliciting, recording, and managing metadata, creating conceptual prototypes and mock-ups, and performing Quality Analyst functions.

8. The role requires a minimum of 10 years of experience in delivering business data analysis artifacts, 5+ years of experience as an Agile Business Analyst, and experience with Azure Databricks, ESRI ArcGIS, enterprise data management, Microsoft Office products, and reporting systems.

9. Preferred skills include strong knowledge of database architectures, strong analytical and problem-solving skills, ability to build strong relationships, prioritize and handle multiple tasks and projects, strong written and verbal communication skills, and a desire to learn, innovate, and evolve technology.

10. The role requires extensive familiarity with ETL, data warehousing, and business intelligence tools such as Business Objects, PowerBI, and Tableau, and experience with key data warehousing architectures including Kimball and Inmon.

11. Technologies required include Data Factory v2, Data Lake Store, Data Lake Analytics, Azure Analysis Services, AZURE Synapse, IBM Datastage, Erwin, SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL, Azure SQL Database, Azure SQL Datawarehouse, operating system environments (Windows, Unix, etc.), and scripting experience with Windows and/or Python, Linux Shell scripting.