The Data Architect is a key member of the Fortna Warehouse Execution System (WES) team that identifies, categorizes, organizes, and validates data and transforms that data into meaningful information. This position plays a vital role in building the Business Intelligence capability of the FortnaWES software product.
PRIMARY RESPONSIBILITIES INCLUDE
Evaluate business and technical domains to produce representative logical and physical data models.
Build data models with the flexibility to change when business requirements change.
Define modeling standards, guidelines, best practices and approved modeling techniques.
Reconcile multiple logical source models into a single, logically consistent enterprise model.
Identify significant enterprise data assets as determined by the business impact, decision impact, risk mitigation or organizational impact of the information.
Establish Master Data Management of significant data assets, and reference data, and lead the stewardship committee.
Cultivate and manage data governance practices.
Lead data integration, business intelligence (BI) and enterprise information management programs by rationalizing data processing to support reuse.
Create data stores, including warehouses, data lakes, data marts, etc., to support the BI initiatives.
Collect and identify the various metadata assets.
Model the future state of the data architecture and provide data architecture best practices and guidelines.
Ensure that critical information assets modeled as part of any project are represented in the enterprise information architecture (EIA) and follow the design guidelines and requirements of EIA.
Offer thought leadership regarding database design, data modeling, security, integration, mining, and advanced analytics techniques
Employ initiative, professionalism and self-discipline in daily interactions.
REQUIRED QUALIFICATIONS
4 Year College Degree (Computer Science or related engineering field).
5+ years of conceptual, logical, and physical modeling, particularly for rationalizing data objects.
Proven capability for managing data migrations between software products and custom apps.
Ability to define the value of the data asset to the enterprise.
Ability to collaborate with business stakeholders, analysts, and data stewards to assess whether the model is fit for use.
Familiar working in Linux environments using open source software tools.
Experienced with Extract-Transform-Load (ETL), Extract-Load-Transform (ELT), and Discover-Access-Distill (DAD) processes.
Extensive expertise in multidimensional data modeling, start schemas, snowflakes, normalized and de-normalized modes, and Kimball methodologies.
Strong negotiation and consensus building abilities.
Exceptional ability to communicate in a written, spoken, or visual manner at all personnel levels.
Able to travel up to 20%, international and domestic.
Ability to perform essential functions of the job.
Desired qualifications:
Demonstrated real-world execution implementing data warehouses and data lakes.
Familiarity working with open-source Linux-based technologies.
Verifiable record of building an enterprise analytics capability from greenfield.
