Architect- Business Intelligence

Job Description Data Platform Solution Architect (Azure Synapse & Databricks) Role Overview We are looking for an experienced Data Platform Solution Architect to join an existing enterprise data platform team. The role requires the ability to rapidly assimilate a complex, partially implemented platform understanding what has been built, what remains, and what needs to evolve and to translate that into a clear, actionable architecture that guides the team through current delivery and the next stage of platform transformation. This person will work closely with senior engineers and stakeholders, providing the architectural vision and technical direction needed to complete ongoing work and design the path forward. Key Responsibilities Rapidly assess and develop a deep understanding of the current platform state across all layers and components, working alongside the existing engineering teamDefine and own the target-state architecture, bridging the gap between what is currently implemented and what needs to be completed or evolvedDesign the architectural roadmap for the next stage of platform transformation, ensuring continuity with current investments while enabling future scalabilityTranslate business and data requirements into architectural decisions, reference designs, and technical standardsProvide hands-on architectural guidance to engineering teams on a day-to-day basis not limited to design documents but actively engaged in deliveryIdentify architectural risks, dependencies, and trade-offs across the platform and recommend mitigation strategiesDefine integration patterns, data flow designs, and governance standards across source ingestion, transformation, and consumption layersEstablish and enforce architecture principles, design patterns, and platform standards across the teamCollaborate with data governance, business, and technology stakeholders to align platform direction with enterprise requirementsSupport migration planning by defining target architectures, transition states, and validation strategies for workload migrations across platformsDrive decisions on platform tooling, infrastructure, and service selection in alignment with cloud and enterprise architecture standards Core Technical Skills Architecture & Design Proven experience designing enterprise-scale data platform architectures end-to-end from source ingestion through to consumptionDeep understanding of medallion / lakehouse architecture patterns (Raw / Harmonized / Conformed / Consumption)Strong knowledge of data modelling approaches: relational, dimensional, and lakehouse-orientedExperience designing data governance architectures: lineage, data quality frameworks, audit and control patterns, SCD versioning, CDCAbility to design for both batch and real-time data processing at scaleExperience architecting parallel-run and phased migration strategies across platformsAzure Data Platform Strong hands-on knowledge of:Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool)Azure Data Lake Storage Gen2Delta Lake on Azure (Synapse Lakehouse)Azure Analysis ServicesOracle Golden Gate or equivalent real-time replication patternsPower BI and semantic layer designDatabricks & LakehouseHands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog preferred)Strong understanding of Databricks platform capabilities: Delta Lake, Spark-based transformation, workflow orchestration, governanceExperience designing migration architectures from legacy data warehouse or Synapse environments to Databricks LakehouseAbility to architect governance and control frameworks natively within Databricks Cloud & Infrastructure Strong Azure cloud architecture skills security, networking, scalability, and cost optimizationExperience with Infrastructure as Code (Terraform preferred)CI/CD and DevOps practices for data platform delivery (Azure DevOps / GitHub Actions)Containerization and compute management (Docker, Kubernetes awareness)Data Engineering DepthSufficient hands-on engineering background to engage credibly with senior engineers on implementation decisionsStrong Python and SQL skills able to review, challenge, and contribute to code where necessaryExperience with ETL/ELT frameworks, pipeline design patterns, and performance optimization at scaleNice to Have Experience with Unity Catalog and Azure Purview for enterprise data governanceExposure to real-time and streaming architectures (Event Hub / Kafka / Kinesis)Familiarity with MLOps and GenAI platform integration patternsExperience with monitoring and observability frameworks (e.g., Dynatrace)Background in financial services or other regulated industriesExperience & Profile 12+ years of experience in Data Engineering and/or Data Architecture, with at least 45 years in a solution or platform architect roleProven experience joining mid-flight programmes able to quickly understand existing implementations and make sound architectural decisions without Job