Spatial Data Analyst Jobs in Virginia (NOW HIRING)

The Virginia Department of Transportation (VDOT) Information Technology Division (ITD) is seeking a master data analyst with demonstrated experience in data analytics to work as a key member of the enterprise data asset team. This analyst will support teams working in agile (sprint) to analyze datasets to be made available in a cloud-based data management platform that will support the agency to produce master data with data governance. Responsibilities include analyzing source systems which contain a spatial component for candidate datasets; documenting business processes and data lifecycle; developing data requirements, user stories and acceptance criteria; and testing strategies. Develop ETL to extract business data and spatial data and load it into a data warehousing environment. Design and test the performance of the system. Consult with various teams to understand the company’s data storage needs and develop data warehousing options. Deep knowledge of coding languages, such as python, Java, XML, and SQL. Well-versed in warehousing architecture techniques such as MOLAP, ROLAP, ODS, DM, and EDW.

VDOT is a fast-paced organization with very high standards for work quality and efficiency. This position is expected to handle multiple projects, and remain flexible and productive, despite changing priorities and processes. Ongoing improvement and efficiency are a part of our culture, and each team member is expected to proactively contribute to process improvements.

Responsibilities include:

• Work with the project team members and business stakeholders to understand business processes and pain points
• Develop expertise in source system datasets and data lifecycle
• Profile source data which may contain a spatial component; review source data and compare content and structure to dataset requirements; identify conflicts and determine recommendations for resolution
• Conduct entity resolution to identify matching and merging and semantic conflicts
• Elicit, record, and manage metadata
• Diagram current processes and proposed modifications using process flows, context diagrams and data flow diagrams
• Decompose requirements into epics and features and create clear and concise user stories that are easy to understand and implement by technical staff
• Utilize progressive elaboration; map stories to data models and architectures to be used by internal staff to facilitate master data management
• Identify and group related user stories into themes, document dependencies and associated business processes
• Discover and document requirements and user stories with a focus on improving both business and technical processing
• Assist product owner in maintaining the product backlog
• Create conceptual prototypes and mock-ups
• Collaborate with staff, vendors, consultants, and contractors as they are engaged on tasks to formulate, detail and test potential and implemented solutions
• Perform quality analyst functions such as defining test objectives, test plans and test cases, and executing test cases
• Coordinate and facilitate user acceptance testing with business and ensure project managers/scrum masters are informed of the progress
• Designs and develops systems for the maintenance of the data asset program (data hub), ETL processes, ETL processes for spatial data, and business intelligence
• Develop a new data engineering process that leverages a new cloud architecture and will extend or migrate existing data pipelines to this architecture as needed
• Design and supports the DW database and table schemas for new and existing data sources for the data hub and warehouse. Design and development of data marts
• Work closely with data analysts, data scientists, and other data consumers within the business in an attempt together and populate data hub and data warehouse table structure, which is optimized for reporting
• The data developers partner with data modeler and data architect in an attempt to refine the business’s data requirements, which must be met for building and maintaining data assets

Qualifications required:

• The candidate must have a minimum of 10 years of experience delivering business data analysis artifacts
• 5+ years of experience as an agile business analyst; strong understanding of scrum concepts and methodology
• Experience organizing and maintaining product and sprint backlogs
• Experience translating client and product strategy requirements into dataset requirements and user stories
• Proficient with defining acceptance criteria and managing acceptance process
• Exceptional experience writing complex SQL queries for SQL Server and Oracle
• Experience with Azure Databricks, Azure data factory, snowflake
• Experience with ESRI ArcGIS
• Experience with enterprise data management
• Expertise with Microsoft Office products (Word, Excel, Access, Outlook, Visio, PowerPoint, Project Server)
• Experience with reporting systems – operational data stores, data warehouses, data lakes, data marts
• The candidate must have exceptional written and oral communications skills and have the proven ability to work well with a diverse set of peers and customers

Preferred skills:

• Advanced understanding of data integrations
• Strong knowledge of database architectures
• Strong analytical and problem solving skills
• Ability to build strong relationships both internally and externally
• Ability to negotiate and resolve conflicts
• Ability to effectively prioritize and handle multiple tasks and projects
• Strong written and verbal communication skills
• Desire to learn, innovate and evolve technology

Computer skills/MS Office/software:

• Excellent computer skills and be highly proficient in the use of MS Word, PowerPoint, MS Excel, MS Project, MS Visio, and MS Team Foundation Server, which will all be necessary in the creation of visually and verbally engaging ETL, data designs and tables as well as the communication of documentation and reporting
• Deep passion for data analytics technologies as well as analytical and dimensional modeling. The candidate must be extensively familiar with ETL (extraction, transformation & load), data warehousing, and business intelligence tools such as business objects, PowerBI and Tableau
• The candidate must also have vast knowledge of database design and modeling in the context of data warehousing
• Experience with key data warehousing architectures including Kimball and Inmon, and has a broad experience designing solutions using a broad set of data stores (e.g., HDFS, Azure Data Lake Store, Azure Blob Storage, Azure SQL Data Warehouse, Azure Cosmos DB

Technologies required:

• 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.)