Data Platform Lead

Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance & AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.Why This Role MattersAmana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative — from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.Core ResponsibilitiesLakehouse Architecture & DeliveryDesign and deliver end-to-end Databricks lakehouse components — ingestion, transformation, semantic layer, and serving.Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.Contribute to and sign off on reference designs, integration patterns, and architecture decision records.Data Engineering & IntegrationBuild and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.Ensure platform reliability through monitoring, alerting, and structured incident response.AI/ML & Analytics EnablementBuild and operate feature store, MLOps, and LLMOps foundations on Databricks.Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.Data Governance & Trustworthy DataImplement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.Partner with the Data Governance Office to translate live policies into enforceable platform controls.Support regulatory, ethical, and internal compliance obligations across the data estate.Cloud & Cost DisciplineOwn FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.Collaboration & Technical LeadershipWork closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.Provide hands-on technical guidance and code review across the team.Translate business requirements into technical designs with clear delivery outcomes.Required QualificationsMinimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.Practical FinOps outcomes on cloud spend.Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).Excellent written and verbal communication skills across technical and business audiences.Preferred QualificationsDirect experience of a Synapse Analytics to Databricks migration.Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.Familiarity with Power BI semantic models and enterprise BI governance.Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.Multi-entity, multi-country group exposure with mixed data residency considerations.Industry experience in construction, engineering services, manufacturing, energy, or logistics.CertificationsMandatory:Databricks Certified Data Engineer Professional (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)Preferred (one or more):Databricks Certified Machine Learning ProfessionalDatabricks Certified Generative AI Engineer AssociateMicrosoft Certified: Azure Data Engineer Associate (DP-203 / DP-700)Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)Microsoft Certified: Azure Solutions Architect ExpertCertified Data Management Professional (CDMP) — DAMAEducationM.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.