Senior Data Architect

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 Responsibilitie sRapidly assess and develop a deep understanding of the current platform state across all layers and components, working alongside the existing engineering tea mDefine and own the target-state architecture, bridging the gap between what is currently implemented and what needs to be completed or evolve dDesign the architectural roadmap for the next stage of platform transformation, ensuring continuity with current investments while enabling future scalabilit yTranslate business and data requirements into architectural decisions, reference designs, and technical standard sProvide hands-on architectural guidance to engineering teams on a day-to-day basis — not limited to design documents but actively engaged in deliver yIdentify architectural risks, dependencies, and trade-offs across the platform and recommend mitigation strategie sDefine integration patterns, data flow designs, and governance standards across source ingestion, transformation, and consumption layer sEstablish and enforce architecture principles, design patterns, and platform standards across the tea mCollaborate with data governance, business, and technology stakeholders to align platform direction with enterprise requirement sSupport migration planning by defining target architectures, transition states, and validation strategies for workload migrations across platform sDrive decisions on platform tooling, infrastructure, and service selection in alignment with cloud and enterprise architecture standard s Core Technical S killsArchitecture & D esignProven experience designing enterprise-scale data platform architectures end-to-end — from source ingestion through to consum ptionDeep understanding of medallion / lakehouse architecture patterns (Raw / Harmonized / Conformed / Consump tion)Strong knowledge of data modelling approaches: relational, dimensional, and lakehouse-ori entedExperience 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 plat formsAzure Data Platform Strong hands-on knowledg e of:Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool)Azure Data Lake Storage Gen2Delta Lake on Azure (Synapse Lakeh ouse)Azure Analysis Ser vicesOracle Golden Gate or equivalent real-time replication pat ternsPower BI and semantic layer d esignDatabricks & Lake houseHands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog prefe rred)Strong understanding of Databricks platform capabilities: Delta Lake, Spark-based transformation, workflow orchestration, gover nanceExperience designing migration architectures from legacy data warehouse or Synapse environments to Databricks Lake houseAbility to architect governance and control frameworks natively within Datab ricks Cloud & Infrastr uctureStrong Azure cloud architecture skills — security, networking, scalability, and cost optimi zationExperience with Infrastructure as Code (Terraform pref erred)CI/CD and DevOps practices for data platform delivery (Azure DevOps / GitHub Ac tions)Containerization and compute management (Docker, Kubernetes awar eness)Data Engineering DepthSufficient hands-on engineering background to engage credibly with senior engineers on implementation dec isionsStrong Python and SQL skills — able to review, challenge, and contribute to code where nec essaryExperience with ETL/ELT frameworks, pipeline design patterns, and performance optimization at scale Nice to HaveExperience with Unity Catalog and Azure Purview for enterprise data gov ernanceExposure to real-time and streaming architectures (Event Hub / Kafka / K inesis)Familiarity with MLOps and GenAI platform integration p atternsExperience with monitoring and observability frameworks (e.g., Dyn atrace)Background in financial services or other regulated ind ustries Experience & Profile12+ years of experience in Data Engineering and/or Data Architecture, with at least 4–5 years in a solution or platform archit ect roleProven experience joining mid-flight programmes — able to quickly understand existing implementations and make sound architectural decisions without starting from a bla nk slateTrack record of delivering architecture across complex, multi-layer data platforms in enterprise envi ronmentsStrong ability to balance pragmatism with rigour — delivering architecture that works for the team today while keeping the longer-term directi on soundExcellent communication and stakeholder management skills — able to present technical architecture clearly to both engineering teams and non-technical stak eholdersCollaborative by nature — this is a working architect role embedded with the team, not a remote advisory positionExperience working in regulated or enterprise-scale environments (financial services a plus)