Senior Data Analytics Architect
4 days ago
Primary expectations:
- Ensure the Data Analytics strategy aligns with the business strategy while shaping the existing ecosystem (data warehouse, MDM, operational data stores), reflecting and addressing constraints as necessary, ensuring minimization of technical debt.
- Meet with business partners, elicit feedback and incorporate requirements into the strategy.
- Implementing and enabling a full analytics data lifecycle
- Apply techniques for achieving high levels of functional cohesion and low coupling to achieve maximum agility and speed to market.
- Manage competing requirements around end-user performance, information security and scalability.
- Define and communicate an actionable Target State Data & Analytics Architecture and provide the transparency, communication and leadership necessary to lead the organization to success.
- Think and act with a sense of innovation, incorporating industry trends.
- Use expertise in data and analytics technologies as well as key industry-standard technologies.
- Work closely with IT and multiple business teams to support design standards and provide technical leadership, process governance, mentoring, and training.
- Evaluate proposed system changes on development and design standards to determine effort, impact, and timeline within their areas of responsibility.
- Interpret requirements (written or oral) into technical specifications for Enterprise standards and governance and manages changes when necessary.
- Support full development lifecycle and has technical knowledge of all phases of application development (design, code, test, debug, documentation, deployment).
- Has and maintains a current working knowledge of data architecture and technologies.
- Update the Performance Objectives/Evaluation document.
- Expert with Data Architecture domains and software development in the Data Analytics space, including data warehouses / data marts using traditional architectures, analytic solutions using Big Data architectures and enterprise-level data architectures
- Expert experience in data management (data warehousing, data mastery, operational data stores, enterprise reporting, Big Data, MapReduce, data discovery, predictive and prescriptive analytics, architecture governance, reference data, metadata and data quality)
- Knowledge of architectural frameworks (e.g. TOGAF, Zachman)
- Enterprise Architecture experience
- Mastery of Integration Architecture, especially Service Oriented Architecture (SOA) and Extract, Transform, Load (ETL).
- Experienced with Infrastructure Architecture, especially Cloud, IaaS, PaaS and SaaS.
- Expert knowledge of modern data analytics technologies while staying current on architecture design and techniques.
- Must possess excellent interpersonal and communications skills, excellent problem solving skills, and the self-motivation to improve skills and abilities.
Kendall & Davis, Inc. has been in business since 1978. Our business niche is Data Warehouse, ETL, Business Intelligence, Cyber Security, & Enterprise Data Architecture. We understand the potential risks technologists experience during any employer transition. We will discuss your career goals in detail prior to evaluating any potential opportunity.
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