FTE - Client
Under minimal supervision, the Analytics Data & Solutions Architect II provides vision, direction, as well as hands-on technical expertise in designing and building analytics solutions that support enterprise decision support, strategic insights and data science initiatives. In partnership with Enterprise Architecture and IT Engineering teams, this role will drive our analytics technology roadmap, aligning information assets and analytics capabilities to achieve business objectives of strategic initiatives, programs and projects leveraging the powerful capabilities of a modern analytics platform.
Essential Duties and Responsibilities:
- Drives the enterprise analytics architecture to support enterprise insights and decision-making architecture leveraging established architecture disciplines.
- Leverages knowledge of the organization’s information, application, and infrastructure environment as well as the current technology landscape to design a holistic and optimized analytics platform.
- Define strategies to operationalize analytics supporting capabilities in discovery, analysis, and reporting across business segments.
- Analyze, shape, and prioritize data and analytics technologies to business capabilities aligning to current requirements along with future needs without significant rework.
- Perform hands-on solution design, solution architectures, architecture roadmaps, prototyping, proof-of-concepts, and development tasks as required in support of projects and products as requested.
- Develops SQL queries to extensively to research, understand and relate distributed data repositories across enterprise.
- Develops and documents data models; ensuring that data is defined and searchable; collaborates with various users across the organization to capture output/ process changes and revise data models.
- Supports Data Science team in the approach to implement advanced analytical models and supporting data pipelines as well and developing the strategies and approaches for Analytics as a Service.
- Ensures accurate documentation of data assets; identifies critical gaps in information domain through a combination of workshops, interviews and internal analysis of various documentation.
- Partners effectively with MDM (Master Data Management), Data SMEs and other stakeholders (Sponsors, Product solutions architects etc.) to design solutions, including identifying and filling critical gaps.
- Develops and maintains data artifacts and acts as a liaison between ETL, integration, Data Science and BI team(s) to support development of data solutions.
- Plan, design, and monitor these security, usability and stability of the analytics platform to help ensure that it complies with enterprise standards and that it performs adequately as additional analytics solutions are implemented.
- Act as a liaison between Technical team, Functional team, Business Functions, and System Integrators to drive architecture solutions.
- Document and proficiently explain complex architectures to technical and functional peers and-as needed--to other levels of the organization.
- This position requires a minimum of five years progressive Analytics architecture experience.
- This position requires a minimum of five years’ experience with business process design and improvement.
- Experience in developing integrated solutions involving process, data, and technology
- Strong conceptual, strategic thinking, problem solving, technical, and analytical skills
- Corporate retail experience is preferred including, but not limited to, data handling in a cloud-based environment, data governance, data quality and in database management and operations.
- Proven understanding of end-to-end flows and processes of enterprise data.
- Proven ability to collaborate with data guru's and developers across the organization.
- Hands-on / In-depth experience in following tools, technologies & Concepts such as, SQL (advanced level), Data management, Master Data Management (preferred customer data focus), Business Intelligence, SOA, Microservices and Content Management.
- Hands on experience in data profiling, data extraction and data validation.
- Understanding of Data Science methodologies/concepts including general statistical concepts, machine learning, feature engineering and artificial intelligence.
- Demonstrated experience of metadata concepts including but not limited to items collection, repositories, technical and/or business content and data lineage.
- Experience in creating logical and physical data models are required. Understanding of Kimball’s methodology is required.
- Experience working with data lake(s) and understanding of various frameworks and methodologies used around Hadoop or Hadoop like systems.
- Experience working in mission critical ODS and Enterprise Data Warehouse environments.
- Experience with AWS frameworks, data tools and environment.
- Understanding of data architecture practices and governance methodologies.
- Proficiency with Microsoft Office, including skills with Word, Excel, SharePoint, PowerPoint, and Visio is required.
- Proven understanding of project management and the software development lifecycle is required.
- Demonstrated business acumen with knowledge and understanding of business issues, priorities, goals, and strategy is necessary.
- Demonstrated ability to communicate across all levels of the organization, presenting complex ideas concisely and clearly articulate ideas verbally and in writing is necessary.
- Proven ability to work efficiently and accurately under pressure, meet deadlines and present a professional demeanor is essential.
- Customer service skills, including the ability to manage and respond to different customer situations while maintaining a positive and friendly attitude are essential.
- In addition, organizational and problem-solving skills, a can-do attitude, and the ability to adjust to changing requirements are essential.
This position requires a Bachelor's Degree in information technology, Computer Science, Computer Engineering, Data Science, Statistics, Mathematics or a related field, or equivalent work experience.