• Capture current and define future state enterprise information architecture and information value chains in collaboration with business and IT teams
• Define strategies and approaches to advance enterprise data platforms in support of the information value streams. 
• Develop the architecture roadmap and plan.
• Collaborate with Enterprise Information Management and Information Security to scope and classified data assets that are deemed enterprise-significant determined by business impact, decision impact, risk mitigation impact, or organizational impact.
• Define and establish data and tech standards for enterprise data acquisition, cleansing, harmonization, storage, aggregation, transformation and consumption.
• Facilitate and collaborate with Enterprise Information Management to deploy standard solutions for data governance.
• Work with cross functional architects to define reference architectures for data placement, usage, integration and storage.
• Establish uniform and consistent identifiers, formats and protocols necessary for sharing and exchanging data (including structured and unstructured).
• Define specifications and publish standards around data transport and data APIs
• Develop business proposal presentations that speaks to both IT and business value.
• Collaborate with engineering, product management, and operations to understand the current data landscape.
• Take accountability for architecting and designing the go-forward data architecture
• Identify new technologies that can be utilized to improve data reliability, quality, scalability, performance, and maintainability
• Ensure the technical feasibility of the data architecture defining
• Oversee the execution of the data architecture from a technical perspective
• Resolve roadblocks and escalate to management 
• Support quality control practices to validate the data resident in the go-forward architecture
• Design a flexible data architecture that enables new, related, data sets to be added onto the existing design
• Seek opportunities for automation
• Guide and mentor junior team members

Skills: Enterprise Information Architecture, Data Platform Strategy, Architecture Roadmap Development, Data Classification, Data Standards Definition, Data Governance Solutions, Data Integration Architecture, Business Proposal Development

• Aligning the data strategy to the business outcomes
• Supporting the development of the data framework for the enterprise solution
• Supporting the development of an enterprise-level data strategy
• Developing, documenting and validating the data conversion/migration strategy, including the data conversion/migration scope, risks, constraints, dependencies and assumptions
• Leading the definition of enterprise principles and standards related to data design, development and integration
• Contributing to the definition of enterprise data requirements
• Responsible for the full life cycle of data conversion/migration tasks, including planning, analysis, design and conversion execution
• Collaborate with various stakeholders from business and IT during various phases of the project
• Lead the analysis with regard to databases and software resources required for design, construction, execution and integration
• Contribute to the elaboration of the release strategy for aspects related to the implementation of data resources
• Lead the data and data migration teams
• Create conceptual, logical and physical data models across a variety of storage technologies (RDBMS, NoSQL, data lake/HDFS, etc) and collaborate with various technical teams on implementation.
• Design data models and storage techniques for structured, semi-structured and unstructured data in the data lake
• Develop enterprise and function-specific data architecture principles, guidelines, and standards and publicize them to engineers and data stewards
• Collaborate with security team on storage and accessibility of PII and sensitive data elements.
• Drive architecture decisions on enterprise data flows and data contracts exchanged between systems, including BI
• Provide technical expertise and recommendations on current and emerging data strategies and platform trends.
• Define a framework for data governance and collaborate with data stewards on identifying data retention, data quality, and access management.
• Responsible for data catalog, including organization of and standards for well-defined metadata and defining the process to maintain the catalog as new data elements are introduced.

Skills: Data Strategy Alignment, Data Framework Development, Data Conversion Strategy, Data Migration Lifecycle, Data Design Standards, Enterprise Data Requirements, Stakeholder Collaboration, Data Modeling

• Create and evolve the technology road maps that define company data architectures and enable a solid company data strategy
• Ensure data solutions are built for performance, fault tolerance and security with reusable patterns
• Develop best practices for knowledge and data discovery to deliver impactful data-driven decision support systems, while leading others to technical success by understanding and applying best practices
• Take ownership of defining best practices for change management, source control and deployment methodologies for big data solutions
• Identify and enable data capabilities across the company
• Design integrations with other data sources
• Research, analyze and promote data standards to be used across the company
• Set and lead standards discussions among big data engineers, data scientists and other data engineers across Technology
• Identify and implement build vs. buy strategies with regard to technology
• Monitor and identify performance trends and work with teams to improve processes and procedures
• Partner with business and Technology to deliver road maps
• Work with the team to build a holistic view of the company's strategy, processes, information and information technology assets
• Define best practices and internal guidelines
• Research new technologies and architect data solutions, capture program metrics
• Mentor associate data architects and other team members outside of direct team
• Ensure alignment and close cooperation with the business and IT functions in charge of the data analytics platform implementation specifically with Data Engineers implementing the data pipelines and data transformation processes, and visualization experts setting up dashboards
• Cooperate closely with the Data Governance organization to ensure an optimal integration of data sources.
• Be an integral part of team of enterprise data architects, lead/participate to build the PMI analytical eco-system by modelling data from source systems, integrated layer and data products using relational and big data technologies.
• Ensure alignment with key counterparts as solution architects, data science, BI and implementation project teams to ensure adherence of application with the business data need and with the data architecture standards.

Skills: Technology Roadmaps, Data Solution Design, Best Practices Development, Change Management, Data Integration, Data Standards, Build vs Buy Strategies, Performance Monitoring

• Design and implementation of effective and efficient data infrastructure and data movement solutions in support of the University's strategic goals. 
• Guides the organization’s data-related efforts, champions the use of technology in the data environment and provides a vision for the development of a robust scalable data model.
• Defining vision, strategy, and principles for data management in collaboration with senior executives to support the University's strategies and priorities
• Defining standards for naming, describing, governing, managing, modeling, cleansing, enriching, transforming, moving, storing, searching, and delivering data within the enterprise
• End-to-end data architectural accountability for defining and refining enterprise architecture for data warehousing and business intelligence solutions
• Understanding how data is, or will be, used and implication on people, processes, products, and technology
• Define and develop a data migration or bridging strategy for existing systems that need to migrate to a next generation application software platform
• Define data standards/reference architectures for use by project teams in developing technical designs and work closely with business units to establish and validate data design requirements
• Propose and run/govern the proof of concepts for new technologies which could result in differentiating capabilities for the business
• Deliver well-defined data design documentation and data models that guide and inform project software, development teams
• Define performance and scalability requirements and validate based on performance and scalability testing
• Review Data Warehouse business cases and initiatives to identify, assess, and communicate feasibility, architecture requirements, costs and issues. 
• Provide thought leadership to evolving Data Warehouse/business intelligence (BI) activities.

Skills: Data Infrastructure Design, Scalable Data Modeling, Data Management Strategy, Data Governance Standards, Data Warehousing, Data Migration Strategy, Data Design Documentation, Proof of Concept Management

• Provide collaboration, leadership and governance for shared Data Architecture standards and guidelines that direct the selection, implementation and deployment of technology within the enterprise.
• Consolidate information from various stakeholders to develop a holistic view of the data fabric and ensure this view is in alignment with business and technology needs.
• Document existing data structures, repositories and frequency of updates to develop an Enterprise Data Catalog that can be leveraged across business domains for operational and analytics purposes
• Translate business needs and requirements into innovative technology solutions that balance cost, capability, performance, and time to market.
• Enrich core datasets with machine learning and data science workflows so that enhancements to this data can be used to support multiple business use cases.
• Reduce cost and complexity by identifying and optimizing data flows between business teams.
• Partner with project management, service management and implementation teams to review existing IT processes and procedures and identify ways to monitor and improve them.
• Develop a strategic vision for the management of data within the organization and develop a long-term roadmap for its governance.
• Architect workflow management for data ingestion and data quality automation.
• Examine all elements of the data lifecycle from ingestion through ETL, validation, archival and purge to seek opportunities for efficiencies.
• Ensure the protection of Customer PII data.

Skills: Data Architecture Governance, Stakeholder Collaboration, Enterprise Data Cataloging, Business Requirements Translation, Machine Learning Integration, Data Flow Optimization, IT Process Improvement, Data Governance Strategy

• Implement architecture framework for the creation and maintenance of EIM domains like Enterprise Data Warehouse (EDW), Data Marts, Operational Data Store (ODS), Metadata, and Big Data
• Create, maintain, and govern data architecture blueprints (current, transitional, and future state)
• Reverse engineer existing physical data structures into logical data models. Identify, understand, and document all data sources
• Organize data at the macro level. Maintain enterprise logical and physical data models and related Metadata
• Organize data at the micro level, i.e. physical data model management
• Ensure data standards compliance at a project level - oversee project implementation of data models (logical/physical)
• Recommends and educates data stakeholders on opportunities to provide data reuse, balancing the issues of centralization and replication
• Contribute knowledge of EIM methodology to the project planning process. 
• Work with Data Governance to implement end-to-end data standards through the development lifecycle and implementation
• Collaborate with multiple functions (security, legal, etc.) to establish standards and policies to ensure enterprise information assets are properly classified, secured, protected by appropriate access management and privacy controls (in-flight and at rest)
• Manage information security, which includes information sensitivity analysis and management, access and audit control systems, encryption and other data protection techniques.
• Moving to a API source model
• Analyzing all the point-to-point integrations
• Understanding MuleSoft from an architecture perspective and how to transition from MuleSoft to an API model
• Define data governance from a data piping perspective
• Work with data governance and data lineage teams to determine how data is being consumed and how to make the best use of data catalog and governance tools (Informatica EDC & Axon)
• Define the future of Data movements for the Bank

Skills: Data Architecture Framework, Data Model Governance, Logical Data Modeling, Metadata Management, Data Standards Compliance, Data Reuse Optimization, EIM Methodology, Information Security Management

• Play a central role in the effort to introduce and successfully implement new data infrastructure and technology
• Serve as a trusted technical advisor by providing objective, practical and relevant advice
• Work with business stakeholders to align solutions to business strategy and requirements
• Determine options in making build vs. buy decisions based on business capability model, resource capacity, and risk
• Assess and communicate the business impact of technical options
• Educate stakeholders on the value proposition of data architecture tooling and practices
• Advocate the use of emerging technology for maximizing business benefits
• Create architecture artifacts (logical architecture diagrams, workflows, data flow diagrams, presentations, etc.) effectively communicate solutions to varied audiences
• Ensure reference architecture meets policies and requirements for technical standards, security, operation, and support
• Research, prototype, and document the organization’s best practices based on industry standards for new technology usage
• Lead organization-wide effort to create an enterprise data model 
• Support platform consolidation efforts in migrating to common foundational data models
• Creating, defining, or choosing consistent data storage solutions for applications
• Provide continuity across each major application solution decision
• Build deep relationships with data engineers across the company
• Provide support to development teams for solving enterprise-wide challenging technical problems through the application of prototypes and knowledge of industry best practices
• Mentor others on software design, construction, and development methodologies through one-on-one interaction, meetings, and brown bag sessions 
• Prototype, as needed, to engage with other technical minds and vet solution ideas 

Skills: Data Infrastructure Implementation, Technical Advisory, Business Strategy Alignment, Build vs Buy Decisions, Business Impact Assessment, Data Architecture Advocacy, Architecture Documentation, Enterprise Data Modeling

• Conceptualize, roadmap, and plan the agency’s enterprise data strategy.
• Design and manage the agency’s reference architecture for data marts, warehouses, tooling, and analytic environments.
• Partner with infrastructure architecture to design and direct the implementation of on-premise and cloud-based data technology components.
• Partner with the data and information services team to perform detailed design and implementation of data platform and business solutions.
• Develop, approve, and promote the creation of agency data standards and practices.
• Design, initiate, and support agency data governance needs.
• Maintain awareness of capacity, demand, value and cost, and work closely with the data and information team to optimize ongoing cloud or other expenses.
• Determine the need for and lead the development of agency policy, procedures, and standards for the effective use of data both within and outside of the enterprise.
• Determine the need for, own and oversee the creation of any enterprise schemas, taxonomies, and related master data.
• Participate in technology and data change management efforts.
• Perform as the service architect for ITSM-focused data services.
• Provide data solution architecture support as needed, including analysis of needs, schema design, and ELT/ETL design.
• Remains current on emerging technologies and makes recommendations for pursuing new products and technologies.
• Foster an inclusive and collaborative environment, partnering with data stewards, champions, and owners to build an effective cross-functional team to lead the evolution of the agency’s data needs.

Skills: Enterprise Data Strategy, Reference Architecture Design, Cloud Data Technology, Data Platform Implementation, Data Governance, Data Standards Development, Cost Optimization, Data Policy Management

• Significant experience in enterprise data architecture within information technology programs and services, with demonstrated expertise in enterprise data management and related technologies
• Familiar with cloud-based technologies for the provision of large-scale, secure bulk data holdings
• Expert in Agile development methodology and concepts, information systems and data life-cycle management best practices and methodologies
• Good understanding of Oracle and Microsoft databases, Oracle E-Business Suite, Oracle Cloud, Exadata, MariaDB, DB2, MySQL, SQL Data Warehouse Appliance
• Experience in building and running a high-performance distributed data architecture team
• Experience with at least two enterprise architecture and data modeling tools e.g. ERWIN, Qualiware, Bizzdesign, Sparx
• Expert in database platforms, ETL tools, MDM, query languages, operational data management and model management tools
• Solid understanding of designing data engineering platforms (preferably Cloud-based and Big Data Platforms)
• Experience in data extraction design from enterprise applications like SAP, CRM systems, manufacturing systems like MES, other enterprise data warehouses like SAP HANA/SAP BW and other unconventional data sources like Social Media and other web crawlers/platforms.
• Strong hands-on experience working on data modelling, data management (master, meta data management, dictionaries, data catalogs)
• Experience in exposure to broad range of tools and technologies in the space (standard RDBS like Oracle, SQL and cloud/big data platforms like Hadoop Stack, Talend, SAP-BODS, Kettle, Ni-Fi, Google Big Query/RedShift etc.)
• Comfortable with understanding the needs of advanced analytics solutions (R, SAS etc.) and data mining/analytics techniques and visual analytics tools like Tableau/ Micro-strategy
• Knowledge of Project management background and familiarity with PMI project methodologies and SDLC

Qualifications: BA in Computer Science with 5 Years of Experience

• Experience in information technology systems design experience
• Experience in data architecture and strategy
• Strong verbal, written, and interpersonal communication skills
• Experiencing influencing management on technical or business solutions
• Ability to interact with all levels of an organization
• Experience in one or a combination of the following: systems, applications, or architecture planning
• Experience using an industry-standard database modeling language
• Knowledge and understanding of components such as framework, security or authentication, event-driven architecture and toolsets for problem monitoring and solving
• Knowledge and understanding of Information Technology processes and technologies
• Knowledge and understanding of SOA (Services Oriented Architecture)
• Engineering and architecture experience with big data
• Knowledge and understanding of DevOps principles
• Knowledge and understanding of Cloud computing, PaaS design principles and microservices and containers

Qualifications: BA in Information Systems with 7 Years of Experience

• Experience with architectural patterns, involved in building APIs, microservices, event streams, and high throughput systems
• Experience working within the AWS ecosystem
• Data engineering experience, with knowledge of the Agile development process
• Experience architecting and developing large scale MDM (preferred Informatica), data warehousing, data lake and data integration ‎projects
• Experience with Data governance tools e.g. Collibra
• Experience in performance monitoring and performance tuning
• Experience in software development, solutions architecture, or architect roles
• Experience in designing, developing, and architecting enterprise data systems
• Experience with distributed data management, data storage including databases (Relational, NoSQL), data analysis, data processing, data transformation, high availability, and scalability
• A solid understanding and experience in the reporting domain - operational and analytics
• Experience driving big data initiatives and navigating complex data challenges
• Has a strong understanding of the big data landscape
• Experience working in and with data lakes, data warehouses, streaming platforms, and cloud platforms
• Experience in data mining, machine learning, and data science
• Experience in financial or other regulated domain
• Experience in transformational initiatives, re-imaging on-prem data footprint (tech, data) to the cloud

Qualifications: BA in Data Science with 4 Years of Experience

• Hands-on experience with at least 3 of the following: Data Management, Data Architecture, Data Migrating, Master Data Modelling, Data Quality Management, Information Governance
• Practical leadership in data integration tools (Talend, Informatica, Data Stage, SSIS, or other).
• Practical leadership in master data management and associated tools (Profisee, IBM, Informatica, Talend, etc.)
• Must have a technical background and be able to lead data integration, data modeling, MDM workflow, etc through a firsthand understanding of the work
• A deep understanding of data lifecycle (data profiling, data quality, master data management, data warehouses/marts/staging/ODS)
• Good knowledge of SQL
• Excellent organizational, interpersonal, and oral/written communication skills
• Experience in enterprise data architecture, design patterns, tradeoff analysis and delivery acceleration in cloud-native environments
• Experience in data solutions enabling Analytical, Operational, Data Science, and ML data flows
• Hand on experience in metadata management, metadata-driven automation and developer productivity tooling
• Experience in large-scale event-driven and streaming solutions in cloud native environment
• Experience with advanced SQL and scripting (python/bash etc.) development
• Experience  developing or working with taxonomies/ontologies
• Experience working/collaborating with Master Data Management, Metadata Management and Data Governance
• Excellent verbal and written communication skills

Qualifications: BA in Software Engineering with 6 Years of Experience

• Data architecture experience (modeling, solution design, integration)
• Experience collaborating with distributed teams across Blue Yonder
• Broad understanding of Enterprise Integration Patterns (EIP), integration approaches and transports, and knows how to apply them to the development of data models and workflows
• Familiar with various industry governing bodies such as GS1, OAGIS, and ARTS
• Experience with Agile development (Scrum or Kanban)
• Ability to pick up new technology quickly
• Good analytical and communication skills
• Communication and stakeholder management skills
• Problem-solving skills to develop quick yet sound solutions to resolve complex issues

• Comfortable scripting in Python, PowerShell, and other
• Understanding of dimensional schemas and BI tools.
• Experience with PowerBI, Tableau, Domo, or similar reporting tools.
• Understanding of Big Data concepts, tools, and techniques
• Practical experience with machine learning applications and AI
• Experience working with cloud storage technologies hands-on: S3, Redshift, Snowflake, Azure, other, combination thereof.
• Experience using ETL tools like ADF, OpenPrise, Informatica, scripting, Oracle, other.

Qualifications: BA in Business Analytics with 7 Years of Experience

• Expert in data and analytics at a global services company.
• Experience in the field of Enterprise Data Architecture at a Fortune 500 company with global footprint, part of which must be in the Insurance domain with related data sets
• Proven expert and thought leader in one of the following data and analytics domains: Intelligent automation, artificial intelligence, and big data.
• Experience as a functional team leader
• Experience with Cloud environments 
• Strategic thinking with equally effective execution planning, judgment, and an agile iterative mindset
• Deep appreciation for efficiency and the ability to take a pragmatic approach to product development and reliable enterprise data architecture delivery
• Exceptional communication skills, including the ability to articulate complex data issues and gain support from internal and external and executive stakeholders
• Strong analytical, structured and interdisciplinary way of thinking and working
• Enterprise data architecture experience
• Experience in working with Data mining, Data governance, and Data Science
• Experience with distributed data management, data storage
• Experience in processing and navigating big data challenges

Qualifications: BA in Management Information Systems with 5 Years of Experience

• Experience in creating logical and physical data models, demonstrated experience with relational and star schema data modeling
• Experience with BI implementation and architecture
• Experience with big data, semi-structured data
• Experience with BI tools and visual reporting platforms from an architecture standpoint
• Experience in development of reporting and analytics business capabilities, strategy and roadmap
• Demonstrated competency in accurately identifying the scope of work and preparing thorough, accurate and detailed schedule estimates
• Experience in migrating from on-premise enterprise data warehouse to cloud-based
• Experience with/involvement in creating and implementing data governance
• Familiarity working with one major cloud based data and analytics platform implementation - AWS, Microsoft Azure, or Google Cloud
• Certifications in Data Management or Data Governance 
• Hands-on experience or certification in TOGAF
• A deep understanding of data management and governance principles and practice
• A flair for problem-solving in a dynamic environment.
• Hands-on Technical design/development experience in SQL Server, Azure Blob Storage, Python, Azure Data Factory, Spark/DataBricks, and CI/CD pipelines
• Extensive experience in developing integrations of Azure data platform to various types of external systems and can recommend approaches and technology covering Data Warehousing, Data Lakes, Azure and Management Information.
• Strong technical skills and awareness of current state of business intelligence technologies.

Qualifications: BA in Applied Mathematics with 10 Years of Experience

• Strong focus and ability to design, manage and construct a Dimensional Data Warehouse
• Deep experience with SQL Server Database Engines (MSFT and others)
• Experience with Google’s Cloud Database technologies (Big Query, Looker, Data flow, Etc.)
• Detailed understanding of data governance and data privacy concepts
• Gaming or hospitality domain experience
• Experience with Gaming management systems (GMS) 
• Proven ability to generate sustainable results and increase revenue utilizing sophisticated customer insights and analytics.
• Excellent interpersonal and written communication skills, ability to present complex, technical ideas clearly and concisely manner to non-technical audiences
• Ability to meet deadlines and work on multiple projects simultaneously
• Strong financial and business acumen, and ability to speak about technology in the language of business
• Collaborative team player with a strong work ethic who works effectively in a cross-functional team environment.
• Adept at listening and soliciting feedback from users and stakeholders
• Excellent project management, organization, and follow-up skills
• Excellent people skills
• A leader with substantial experience in Data Analytics, Data modelling and data warehousing
• Strong data modelling skills including complex relationships and historical recording techniques

Qualifications: BA in Statistics with 4 Years of Experience