Job Location:Β Available to
work Hybrid, Richmond, VA.
Β
Note: 10+ yrs. Experienced,
local candidate, In person interview, 3 daysWeek/On-Site
Β
Job Description:
The client is seeking a Master Data Analyst with demonstrated
experience in data analytics to work as a key member of 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
companyβs 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:
Preferred Skills:
Skills Set:
Β
Skill | Required /Desired | Experience |
Designs and develops systems for the maintenance of the Data Asset
Program, ETL processes, and business intelligence | 10 years | |
Design and supports the DW database and table schemas for new and existent
data sources for the data hub and warehouse. Design and development of Data | 10 years | |
Work closely with data analysts, data scientists, and other data consumers
within the business in an attempt to gather and populate data hub and data | 10 years | |
Advanced understanding of data integrations.Β· Strong knowledge of database
architectures, strong understanding of ingesting spatial data | 10 years | |
Ability to negotiate and resolve conflicts,Β· Ability to effectively
prioritize and handle multiple tasks and projects | 10 years | |
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 | 10 years | |
Experience with key data warehousing architectures including Kimball and
Inmon, and has a broad experience designing solutions using a broad set of da | 10 years | |
expertise in Data Factory v2,Data Lake Store, Data Lake Analytics, Azure
Analysis Services, Azure Synapse | 10 years | |
IBM Datastage, Erwin, SQL Server (SSIS, SSRS, SSAS), ORACLE, T-SQL, Azure
SQL Database, Azure SQL Datawarehouse | 10 years | |
Operating System Environments (Windows, Unix, etc.).Β· Scripting experience
with Windows and/or Python, Linux Shell scripting | 10 years | |
Experience in AZURE Cloud engineering | 10 years | |
The candidate must have a minimum of 10 years of
experience delivering business data analysis artifacts | 10 years | |
experience as an Agile Business Analyst; strong
understanding of Scrum concepts and methodology | 5 years | |
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 | - | |
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 β operational
data stores, data warehouses, data lakes, data marts | - |