The opportunity

• CT Assistant Director Data Architect
• Rank: Assistant Director

Your key responsibilities

• Developing large and complex data architecture, composed of models, policies, rules or standards that govern which data is collected and how it is stored, arranged, integrated and put to use in data systems, including the design, build and management of data infrastructure to address business requirements
• Creating sound project plans with the business by engaging with multidisciplinary teams, and by identifying, managing and mitigating risk
• Developing relationships across the business to understand data requirements, applies deep technical knowledge of data management to solve business problems in areas where solutions may not currently exist, necessitating new solutions/ways of working/technologies and proactively articulating these to the business
• Providing innovative and practical designs for the design and integration of new data architecture for the enterprise, applying sophisticated technical capabilities
• Creating, maintaining and supervising on-premise or cloud infrastructure, such as the design of end-to-end data platforms, development and operations of cloud management and design of distributed systems, handling structured and unstructured data
• Inspiring others in resolving sophisticated issues in data architecture and solving sophisticated, escalated aspects of a project
• Designing solutions that will catalog, organize and store an organization's internal unstructured data
• Working across multidisciplinary teams and with the business to define and delivering analytics solutions that will deliver business value
• Supervising the progress and the quality of the project
• Reviewing and developing due diligence to confirm the developed solution align with architectural design
• Understanding how the end-to-end management vision is aligned to the broader organization strategy and objectives
• Contributing to data management standards to promote optimization and consistency

Skills and attributes for success

To qualify for the role you must have

Solution Architecture & Design - Capability to help clients design solution architecture & requirements for feeding into package definition, solution build, etc. Includes technical system architecture, logical data models, networking models, hardware architecture & requirements. Architectures include: Conceptual IS service, Logical application, Physical application, Conceptual data, Logical data, Physical data, Conceptual platform services, Logical technology, Physical technology, Security, Transition, Architecture roadmap.

• Data Architecture and Design - Capability to define the models and standards by which data is sourced, stored, distributed and governed within an organization
• Enterprise Content Management - Capability to define solutions that will catalog, organize and store an organization's internal unstructured information, e.g. word documents, emails etc.
• Master, Reference and Metadata Management - Capabilities to develop solutions that define the master data (internal glossary of key data items), the reference data (external glossary of standard data items and values) and metadata (the data that describes the data set)
• Vendor Package and Partner Selection - Capability to identify software packages and solutions that could meet client solution requirements and develop requests for proposal (RFPs) from these vendors. Assist clients in the evaluation of the resulting proposals, including the package capabilities and fit to the requirements (business and technology), vendor proposals for pricing and support
• Cloud Computing: Good knowledge of Azure Data Platforms. Understand and configure Azure networks and resources. Should be able to design and implement solutions on Synapse, Data Factory, Databricks, Azure AI Studio, Azure Stream Analytics and other Azure platforms.
• Data Access Tools: Azure Data Explorer, Azure Stream Analytics, MS SQL Server Management Studio, SQL Developer, TOAD, Mongo DB Compass, Neo4J Aura.
• Data Modelling Tools: Erwin, Excel, Power Designer, Sparx, Visio
• Data Governance Tools: Microsoft Purview, Collibra.
• Distributed Systems: Azure ADLS Gen 2, Databricks, Hadoop, HDFS, Kafka, MapReduce/Hive, Spark, Storm, Zookeeper
• Enterprise Architecture Tools: Spark Enterprise Architect
• Graph Databases: Should have extensive experience designing and modelling enterprise solutions on the Neo4j graph database, including defining optimal graph schemas, relationship structures, and query patterns. Must possess a deep understanding of Neo4j internals and configurations, such as clustering, memory tuning, performance optimization, and operational best practices. Strong proficiency in Cypher is required, along with hands on expertise using Neo4j Graph Data Science libraries to build advanced analytics and AI driven graph solutions. Should be able to define architectural standards, integration patterns, and governance models for scalable, secure graph based systems.
• Hadoop Distributions: Azure Databricks, Cloudera, Hortonworks, MAPR, Azure Synapse Analytics
• NoSQL Document Stores: Understanding of MongoDB and other NoSQL databases.
• Generative AI: Lead the end to end architecture, design, and governance of enterprise grade Generative AI platforms leveraging RAG (Retrieval-Augmented Generation) and GraphRAG methodologies. Must demonstrate deep expertise in designing scalable retrieval and reasoning systems, orchestrating complex AI pipelines using LangChain and LangGraph, and integrating heterogeneous enterprise data ecosystems—including vector stores, graph databases, relational systems, and unstructured data repositories. Understanding of Model Context Protocol (MCP) servers, with the ability to define standards, patterns, and modular components that enable secure, extensible AI capabilities across distributed environments. Need to provide technical leadership in defining solution blueprints, ensuring that AI systems meet enterprise benchmarks for scalability, reliability, observability, compliance, and interoperability across business platforms.
• DataOps and MLOps: Must possess deep expertise in modern microservices based design and be capable of engineering robust, scalable deployment patterns leveraging Azure Kubernetes Service (AKS). This includes defining CI/CD standards for data and ML pipelines, enabling reproducibility through containerization, governing model lifecycle management, and establishing best practices for automated testing, versioning, lineage, quality, and observability.
• Relational SMP Databases: Azure SQL PaaS, IBM DB2, MySQL, Oracle, PostgreSQL, SQL Server.

What we look for

• Strong analytical skills and problem-solving ability
• A self-starter, independent-thinker, curious and creative person with ambition and passion
• Excellent inter-personal, communication, collaboration, and presentation skills
• Customer focused
• Excellent time leadership skills
• Positive and constructive minded
• Takes ownership for continuous self-learning
• Takes the lead and makes decisions in critical times and tough circumstances
• Attention to detail
• High levels of integrity and honesty

What we offer you

At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

Are you ready to shape your future with confidence? Apply today.

To help create an equitable and inclusive experience during the recruitment process, please inform us as soon as possible about any disability-related adjustments or accommodations you may need.