Data & AI Senior Architecture Consultant

at  NTT Data

MAKE AN IMPACT WITH NTT DATA

Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive.

KNOWLEDGE AND ATTRIBUTES:

• IT Industry and Technology: Extensive understanding of IT industry environment and business needs, extensive understanding of current technologies (see list below) and technology trends and the ability to define relevant policies.
• Enterprise Architecture: Knowledge and practical experience with at least one Enterprise Architecture Framework like TOGAF, Zachman, Gartner Enterprise Architecture Framework etc.
• Project Management: Knowledge of modern PM methodologies like Agile methodologies – Scrum, Kanban, Hybrid methodologies - Agile-Waterfall Hybrid, Scaled Agile Framework (SAFe), etc.
• Consulting Practices: Knowledge of consulting practices like for example Data Strategy Development, AI Readiness Assessment, Data Architecture Design, AI Solution Development, Data Analytics Consulting, Tool and Platform Assessment, etc.
• Technical skills:
• Data Engineering:
• ETL Processes: Experience with Extract, Transform, Load (ETL) processes and supporting tools, for example Apache NiFi, Talend, or Informatica.
• Data Warehousing: Knowledge of data warehousing solutions like Amazon Redshift, Google BigQuery, or Snowflake.
• Data Lakes: Understanding of data lake architectures and technologies such as Apache Hadoop and Apache Spark.
• Data Spaces: Understanding of data spaces concept and familiarity with data spaces design principles and corresponding open source components.
• Machine Learning and AI:
• Frameworks: Knowledge of machine learning frameworks such as TensorFlow, PyTorch, and Scikit-Learn.
• Model Deployment: Experience with deploying machine learning models using platforms like TensorFlow Serving, MLflow, or Kubernetes.
• AI Services: Familiarity with AI services provided by cloud platforms, such as AWS SageMaker, Azure Machine Learning, and Google AI Platform.
• Cloud Platforms:
• AWS: Knowledge of AWS services including EC2, S3, Lambda, RDS, and SageMaker.
• Azure: Knowledge of Azure services such as Azure Data Factory, Azure Machine Learning, and Azure Synapse Analytics.
• Google Cloud: Familiarity with Google Cloud services like BigQuery, AI Platform, and Dataflow.
• Big Data Technologies:
• Hadoop Ecosystem: Understanding of Hadoop ecosystem components such as HDFS, MapReduce, Hive, and Pig.
• Real-Time Data Processing: Experience with real-time data processing frameworks like Apache Kafka, Apache Flink, or Apache Storm.
• NoSQL Databases: Knowledge of NoSQL databases such as MongoDB, Cassandra, and HBase.
• Data Governance and Security:
• Data Privacy: Understanding of data privacy regulations such as GDPR and CCPA.
• Data Security: Experience with data security practices, including encryption, access control, and secure data sharing.
• Data Quality: Knowledge of data quality management practices and tools.
• DevOps and CI/CD:
• Continuous Integration/Continuous Deployment: Experience with CI/CD tools such as Jenkins, GitLab CI, or CircleCI.
• Infrastructure as Code: Familiarity with infrastructure as code tools like Terraform, Ansible, or CloudFormation.
• Containerization: Experience with containerization technologies such as Docker and Kubernetes.
• Software development:
• Technical Evaluation: Expertise in selecting appropriate development stacks and reviewing software architecture.
• Programming languages: Knowledge of any programming languages like Java, Python, JavaScript etc.
• Programming frameworks: Experience with frameworks like Spring Boot for developing microservices and enterprise applications, familiarity with frameworks such as Django or Flask for web development and frameworks and libraries like React, Angular, or Vue.js for building interactive user interfaces.
• Software Architecture Design: Experience in designing and implementing microservices-based architectures. Understanding of service decomposition, inter-service communication, and API gateways.
• Development Tools and Practices: Knowledge of Development Tools and Practices like Version Control systems (Git), automated testing frameworks and tools such as JUnit, pytest, or Selenium.
• Other skills:
• Strong problem-solving and analytical skills.
• Ability to work in high-pressure situations.
• Ability to establish and manage processes and practices through collaboration and the understanding of business.
• Ability to contribute information on relevant vertical markets.
• Ability to contribute to the improvement of internal effectiveness by contributing to the improvement of current methodologies, processes and tools.

ACADEMIC QUALIFICATIONS AND CERTIFICATIONS:

• Master’s degree or equivalent in Information Technology or Computer Science.
• Relevant consulting and technical certifications preferred, for example TOGAF.
• Professional architectural certification is a big plus:
• AWS Certified Solutions Architect - Professional
• Microsoft Certified: Azure Solutions Architect Expert
• Google Cloud: Cloud Architect Professional

REQUIRED EXPERIENCE:

• Advanced experience with a strong background in all aspects of software application development
• Advanced comprehensive technical experience in a similar role within a large scale (preferably multi- national) technology services environment.
• Advanced multi-technology software design experience.
• Advanced expertise coupled with consulting and client engagement experience, demonstrating good experience in client needs assessment and change management.
  Workplace type:
  On-site Working

KEY RESPONSIBILITIES:

• Strategic Leadership: Shapes technological strategies and development process.
• Technology Oversight: Supervises current technologies and defines relevant policies.
• Technical Decision-Making: Makes technology-related decisions aligned with business objectives.
• Technical Leadership: Support Software Development Team for the definition of guidelines for the development process.
• Hiring and Training: Involved in hiring, training, onboarding.
• Customer relationship: Builds and strengthens business relationships with partners and represents the company at conferences and events.
• Data and AI Strategy: Creates and implements strategies to optimize data systems and technologies, evaluates processes and technologies to make meaningful outcome of data.
• Go-To-Market strategy: Participates in strategic planning and goal setting for the Go-To-Market (GTM) strategy.
• Consulting: Acts as a consulting partner for our clients as part of the Data & AI GTM Stream.