Data Architect

Who we are We are seeking an accomplished and highly skilled Snowflake Solution Architect. The successful candidate will bring deep expertise in designing and implementing Snowflake-based cloud data platforms that are scalable, secure, and business-aligned. This individual will play a pivotal role in guiding enterprise clients through their data platform modernisation journey, leveraging Snowflake’s capabilities to enable data democratisation, advanced analytics, and AI-driven insights.

As a trusted advisor, you will collaborate with client partners, business stakeholders, and technology teams to define Snowflake strategies, design robust architectures, and implement best practices. You will thrive in a fast-evolving technology environment, continuously expanding your knowledge to ensure NTT DATA and our clients remain at the forefront of data innovation.

Data Architect designs the high-level, multi-cloud blueprints and strategic vision for the enterprise data lifecycle. This role establishes the architectural patterns, security schemas, governance frameworks, and data models required to support real-time data streaming and multi-cloud portability. The Architect focuses on how data is structured, integrated, and governed across the entire company.

What you'll be doing Enterprise Blueprint & Strategy: Design and maintain scalable, multi-cloud enterprise data lakehouses, data meshes, and distributed storage patterns (e.g., across AWS, Azure, and Google Cloud) Event-Driven Architecture (EDA) Design: Define organizational standards for real-time messaging, schema registries, pub/sub paradigms, and asynchronous data flows Data Modeling & Governance: Create enterprise-level conceptual, logical, and physical data models using Kimball dimensional modeling, Data Vault 2.

0, or Medallion architectures Set strict policies for data quality, security, and regulatory compliance (GDPR/CCPA) Technology Evaluation: Lead the architectural review board to evaluate and select tech stack tools (e.g., Confluent Kafka vs. AWS Kinesis, Snowflake vs. Databricks) Cross-Functional Leadership: Translate complex technical blueprints into business strategies for C-suite stakeholders and guide engineering teams on implementation goals What you'll bring along BSc/MSc in Computer Science, Data Engineering, or related field; Snowflake certifications (Snow.

Pro Core, Advanced) highly desirable Experience: 8–10+ years in data systems, with 4+ years explicitly in enterprise data architecture Cloud Multi-Platform Mastery: Advanced design experience across AWS (S3, Redshift), Azure (Synapse, Data Lake), and GCP (Big. Query), including cross-cloud data replication Streaming Foundations: Mastery of event-driven patterns, change data capture (CDC), dead-letter queues, and event sourcing Tools & Frameworks: High familiarity with Apache Kafka, Apache Iceberg, Delta Lake, Databricks, and infrastructure-as-code (Terraform)