Description
Title: Data Architect
Duration: 9months +
Number of Positions: 1
Years of experience: 8+
Notes:
Self-driven and solution driven individual needed. Main focus will be to drive out the development of an enterprise data model at a conceptual level and a logical level. Will need great communication skills - conducting meetings with development teams, business teams so they can model it correctly. Must have exceptional modelling skills. Must be able to manage certain master data issues that are systemic in business and be able to collaborate with others to find solutions. Must be able to guide team to resolution. Will work with 3-4 people on average on a day to day basis. Manager prefers local candidates at this time. The person will be working with a large amount of information. Responsible for the standardization, consolidation and simplifying business processes. Energy industry knowledge is preferred. Erwin modelling tool experience is preferred.
Data Architect Responsibilities:
- Take ownership of existing client Enterprise data model and continue to vet with the business
- Build out the underlying logical data models for each data domain within the conceptual model
- Manage a roadmap that shows the incremental buildout of the Enteprise model
- Define and document all data elements in the model
- Act as subject matter expert for the EA team and other integration teams that are leveraging the Enterprise model.
- Define enterprise level master data issues and work with the business to drive out the mitigating solution
Technical/Job Competencies:
- Must be a self starter with the ability to work well in a team environment
- Deep data modelling skills, preferably in Erwin
- Ability to work directly with business users to draw out requirements for the Enterprise data model.
- Exceptional communication skills as well as of BI technologies/tools
- Ability to work effectively on tight deadlines as necessary
Job Qualifications:
- 6+ years of extensive work developing large scale data models
- Experience with Master Data and data quality best practices
- Prior Oil and Gas industry knowledge