Senior Data Architect - Azure

Employment: Full-time Experience: Mid-Senior level The Senior Data Architect is responsible for designing and delivering enterprise-scale cloud data architectures aligned with business objectives and regulatory requirements. This role leads data architecture initiatives across pre-sales and delivery, covering data modelling, integration, governance, and cloud data platforms. It also enables AI/ML and Generative AI solutions by building scalable, secure, and high-performance data foundations while providing technical leadership and architectural guidance to engineering teams and clients. Responsibilities: Define target-state data architectures, including data lakehouse, data warehouse, streaming, and Master Data Management (MDM) solutions. Lead architecture workstreams across pre-sales and delivery, including discovery workshops, current-state assessments, solution blueprints, and effort estimation. Design conceptual, logical, and physical data models and integration patterns for batch, micro-batch, and real-time data pipelines. Establish and implement data governance frameworks covering data quality, lineage, cataloguing, security, and access control. Guide engineering teams on implementation standards, architecture reviews, code reviews, and data platform performance optimization. Design data foundations for AI/ML and Generative AI use cases, including feature stores, vector databases, and Retrieval-Augmented Generation (RAG)-ready data pipelines. Act as a trusted technical advisor to client Chief Data Officers (CDOs), heads of data, and enterprise architects. Present and justify architecture decisions to technical and executive stakeholders. Develop reusable accelerators, reference architectures, and data practice standards. Our Culture & Code of Conduct: At ZainTECH, we take pride in a culture built on collaboration, innovation, and uncompromising integrity. We are looking for individuals who share these values and are committed to customer-centricity and ethical excellence. All employees are expected to uphold our Code of Conduct, which serves as a guiding framework for responsible behavior across everything we do — from ho we work with each other to how we engage with clients and partners globally. Requirements 8+ years of experience in data engineering or data platform roles, including at least 4 years as a Data Architect on enterprise-scale programmes. Proven experience designing and delivering end-to-end cloud data platforms covering ingestion, storage, transformation, serving, and consumption. Strong expertise in data modelling methodologies, including Kimball/dimensional modelling, Data Vault, and Third Normal Form (3NF). Advanced SQL skills and experience with distributed data processing technologies such as Apache Spark. Experience with modern lakehouse table formats, including Delta Lake, Apache Iceberg, or Apache Hudi. Strong understanding of data governance, security, and privacy practices, including RBAC, encryption, masking, personally identifiable information (PII) handling, and regulatory compliance. Proficiency in Python for data engineering and automation, with an understanding of CI/CD and infrastructure-as-code concepts. Experience with streaming technologies such as Apache Kafka, Azure Event Hubs, or equivalent platforms. Excellent English communication skills, with the ability to translate business requirements into technical architectures and justify design decisions. Consulting or client-facing delivery experience, preferably across multiple industries. Hands-on experience with Microsoft Fabric and/or Azure Synapse Analytics. Experience with Azure Databricks, including Unity Catalog, Delta Live Tables, and workspace administration. Knowledge of Azure Data Factory or Microsoft Fabric Data Pipelines for orchestration and integration. Experience designing Azure Data Lake Storage Gen2 architectures and data zones, including raw, curated, and consumption layers. Familiarity with Microsoft Purview for data governance, cataloguing, and lineage. Experience with Azure SQL, Cosmos DB, Azure Event Hubs, and Stream Analytics. Exposure to Azure AI services, including Azure OpenAI, Azure AI Search, vector search, and Azure Machine Learning. Knowledge of Azure landing-zone and platform design, including networking, private endpoints, Microsoft Entra ID, Key Vault, and cost management. Relevant Microsoft certifications, such as DP-600, DP-203, or AZ-305. Experience with the Cloudera platform, including CDP, Cloudera Data Engineering, HDFS, Hive, Impala, NiFi, and Ranger, across on-premises or hybrid deployments.