Enterprise Data Architect in Omaha, NE

View All Healthcare jobs


Healthcare   •  

Less than 5 years

Posted 7 weeks ago

As Enterprise Data Architect, you'll be providing architectural guidance, technological recommendations and strategies that support the development and maintenance of flexible data architectures and data flows supporting BI\EDW solutions. This includes, but is not limited to, building, deploying and maintaining: ETL processes, external and internal electronic data interchange processes, data quality methods, transactional interfaces, data modeling, EDW architectures, data marts, and data tool\system administration. This role involves interactions with all business areas within Home Instead and includes being a subject matter expert, customer advocate, communicator, and decision maker.

In addition, the Enterprise Data Architect also . . .

  • Provides technical leadership regarding data strategy and road map exercises, data architecture definition, business intelligence/data warehouse product selection, design and implementation for the enterprise.
  • Creates and maintains standard techniques for data modeling, process modeling, master data management, metadata management and enterprise data management.
  • Creates and maintains a data solution life cycle: analyze/profile data, create conceptual, logical & physical data model designs, architect and design ETL, reporting and analytics solutions.
  • Manages and maintains the data models and associated metadata for the enterprise.
  • Participates and provides technical leadership in all phases of a project from discovery and planning through implementation and delivery; facilitate the discovery of entities, attributes, relationships, and business rules from the functional experts and the lines of business.

What does a successful Enterprise Data Architect candidate look like?

  • Experience working in a team-oriented, collaborative environment.
  • Strong interpersonal and communication skills.
  • In-depth knowledge of modeling methodologies and techniques; Hands-on experience with modern enterprise data architectures and data toolsets (ex: data warehouse, data marts, data lake, 3NF and dimensional models, modeling tools, profiling tools).
  • Strong programming background. Experience with and the ability to troubleshoot and tune relevant programming languages like SQL, Python, Java/Scala/Ruby, R, PIG Latin, HiveQL & MapReduce.
  • Strong understanding of Master Data Management disciplines and methodology.
  • Good understanding of ETL processes and ETL best practices.
  • Experience with Agile practices, CI/CD, and source control.
  • Experience / familiarity with Business Intelligence tools. For example: MS Power BI.
  • Experience / familiarity with Hadoop, Big Query, Redshift, Azure, Big Data and Cloud Architecture is a plus.