Data Platform Solution Architect

Job description

**Architecture & Design** - Proven experience designing enterprise-scale data platform architectures end-to-end from source ingestion through to consumption - Deep understanding of medallion / lakehouse architecture patterns (Raw / Harmonized / Conformed / Consumption) - Strong knowledge of data modelling approaches: relational, dimensional, and lakehouse-oriented - Experience designing data governance architectures: lineage, data quality frameworks, audit and control patterns, SCD versioning, CDC - Ability to design for both batch and real-time data processing at scale - Experience architecting parallel-run and phased migration strategies across platforms - Azure Data Platform Strong hands-on knowledge of: - Azure Synapse Analytics (Pipelines, Spark Pool, Dedicated SQL Pool) - Azure Data Lake Storage Gen2 - Delta Lake on Azure (Synapse Lakehouse) - Azure Analysis Services - Oracle Golden Gate or equivalent real-time replication patterns - Power BI and semantic layer design - Databricks & Lakehouse - Hands-on experience with Azure Databricks (Delta Live Tables, Unity Catalog preferred) - Strong understanding of Databricks platform capabilities: Delta Lake, Spark-based transformation, workflow orchestration, governance - Experience designing migration architectures from legacy data warehouse or Synapse environments to Databricks Lakehouse - Ability to architect governance and control frameworks natively within Databricks **Cloud & Infrastructure** - Strong Azure cloud architecture skills — security, networking, scalability, and cost optimization - Experience 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 Depth - Sufficient hands-on engineering background to engage credibly with senior engineers on implementation decisions - Strong Python and SQL skills — able to review, challenge, and contribute to code where necessary - Experience with ETL/ELT frameworks, pipeline design patterns, and performance optimization at scale **Nice to Have** - Experience with Unity Catalog and Azure Purview for enterprise data governance - Exposure to real-time and streaming architectures (Event Hub / Kafka / Kinesis) - Familiarity with MLOps and GenAI platform integration patterns - Experience with monitoring and observability frameworks (e.g., Dynatrace) - Background in financial services or other regulated industries **Experience & Profile** - 12+ years of experience in Data Engineering and/or Data Architecture, with at least 4–5 years in a solution or platform architect role - Proven experience joining mid-flight programmes — able to quickly understand existing implementations and make sound architectural decisions without starting from a blank slate - Track record of delivering architecture across complex, multi-layer data platforms in enterprise environments - Strong ability to balance pragmatism with rigour — delivering architecture that works for the team today while keeping the longer-term direction sound - Excellent communication and stakeholder management skills — able to present technical architecture clearly to both engineering teams and non-technical stakeholders - Collaborative by nature — this is a working architect role embedded with the team, not a remote advisory position - Experience working in regulated or enterprise-scale environments (financial services a plus)