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.
- 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.
- 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.