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 our existing data pipelines to this architecture as needed.
Design and support 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 to together and populate data hub and data warehouse table structure, which is optimized for reporting.
The Data developers partners 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
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.).
Scripting experience with Windows and/or Python, Linux Shell scripting
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