Technical Data Architect

Responsibilities
• Deliver thought-leadership, turning abstract and logical concepts into IT solutions, which are usable, integrated and secure from day-one
• Develop architectural runway for Safe Program Increment (PI) and Sprint planning for enterprise initiatives
• Identity, architect and align:
• Development tools and languages for front-end (Web, Android and Apple iOS) and server-side solutions
• Patterns and best-practices for multi-tiered distributed applications, integration, information security
• Globally distributed and accessed multi-tenant applications
• Property-graph, NoSQL and Relational database design, Discrete and streaming data ingress, storage and archive
• Patterns and best-practices to establish data pipeline with data snapshots
DevOps tools, and tool-chaining to achieve end-to-end automation
• Big-data techniques, leading to rapid integration with machine-learning and related AI tools
• Experience or knowledge in Azure Cloud architecture, design and development practices enabling:
• Multi-experience App architecture: Cloud-native app stack, Web and Mobile app stack
• Data architecture patterns and practices
• Microservices and Micro frontend architecture, APIs, Services
• Event-driven architecture, Agile practices, DevSecOps, Continuous Integration and Continuous Delivery
• Modernizing legacy application architecture patterns
• Participate with SMEs and Information Technology team members in the development of system solution architecture of applications and technology components. These activities will include:
• Evaluating services and applications, with proof-of-concepts and desktop exercises
• Preparing material for Change Management and communication, vendor engagements such as statement of work
• Leading prototyping activities related to IT processes, tools and software development based on future-state process definition, gap analysis, application requirements and associated software development
• Leading the development of future state patterns and tools enabling rapid development of data centric solutions
• Leading solution design and development of highly-performing business applications


Basic Qualifications
• Bachelor's degree in Computer Science, Computer Engineering, CIS, MIS or another field of study
• 10+ years functional, Information Systems and Technology (IS&T) or automation experience in the EPC or related industries.
• Have deep technical understanding, in-depth knowledge and experience in one or more of the following technologies:
• Azure Cloud services: Web and Mobile Apps, Databases, Integration, Developer Tools SQL, NoSQL, Neo4j Graph, Triple Store and Document databases
MDM: Master, Reference and Metadata Management, Data Quality, Integration, Interoperability
• Business Process Automation, Process Orchestration and integration with UI/UX, Smart Machines
• Identity and Access Management: authentication, authorization
EPC industry applications and tools
• Hands on experience in designing, coding, coaching and implementing one or more of the following technologies and languages:
• Azure PaaS services for cloud-native App development
• NodeJS, JavaScript, ReactJS, Kotlin, .NET, Java, Python, JSON, JSON-LD, GraphQL
Mobile, web and server-side development patterns
• BPMN 2.0, workflow engines
• Integration and interoperability
Experience and or understanding of data-centric design and execution
Strong communication skills
Ability to think out of the box and questioning everything



Preferred Qualifications & Skills


Data Engineering experience develop and implement data models, database design, query plan and database components, with experience in:
Data Quality for data ingress in data pipeline
Data models for Property-Graph databases
Master, Reference and Metadata Management, Data Integration and Interoperability
Query Languages for Property-Graph (Neo4j Cypher) or Knowledge-Graph, NoSQL, and Relational databases
Large Data technologies with Azure Data Factory, Databricks
Good understanding of the information lifecycle of project data - how information is exchanged between functions/disciplines and ownership of data transitions throughout the life of a project.
Excellent automation skills. Good understanding of the link between work process and tools. Strong skills around using tools to create, view and edit data.
Technical knowledge of functional processes and systems, processes, and applications for engineering and construction methods and materials, usage of engineering applications to produce deliverables.
Knowledge of data governance, master data management, and data quality.
Knowledge of Semantic Web, ontologies and associated technologies.
Knowledge of enterprise systems monitoring and service level management.
Knowledge of Design Thinking.