Senior Data Architect

Overview Gravitas is seeking a Senior Data Architect to lead the design and delivery of modern data platforms and analytics architectures within a fast-paced, client-facing environment. You will act as the Databricks champion within the business, shaping best practice, guiding delivery teams, and supporting stakeholders through pre-sales and solution definition. Key ResponsibilitiesOwn end-to-end data architecture across lakehouse, warehouse, and streaming patterns, ensuring scalability, security, and governance.Act as Databricks champion: define standards, reference architectures, accelerators, and reusable assets.Lead architectural design for Databricks (workspaces, clusters, jobs, Delta Lake, Unity Catalogue, MLflow) and integrations with cloud services.Partner with pre-sales teams to shape propositions, run discovery, produce high-quality proposals, and present solutions to senior client audiences (pre-sales experience is essential).Translate business requirements into target-state

data models, ingestion patterns, and semantic layers.Guide engineers on implementation, performance optimisation, cost control, CI/CD, and operational readiness.Ensure compliance with data governance, privacy, and security controls (RBAC, encryption, auditing, lineage). Essential RequirementsSignificant Databricks experience required, including production-scale deployments and optimisation.Strong hands-on capability with Spark/SQL, Delta Lake, orchestration, and data engineering patterns.Prior experience within a consulting practice with exposure to both pre-sales and delivery leading on RFI and RPF responses, discovery, risk and high-level estimates.Extensive experience designing cloud data platforms (AWS, Azure, or GCP) and integrating with enterprise systems.Proven stakeholder management and ability to communicate architecture to both technical and non-technical audiences.Experience with data modelling (dimensional, Data Vault, and/or domain-oriented approaches) and metadata management.Working knowledge of DevOps practices, infrastructure as code, and automated testing for data pipelines. DesirableDatabricks Certifications highly desired (e.g., Data Engineer, Data Analyst, Machine Learning, or Architect).Experience delivering governance frameworks, catalogue implementations, and operating models.Exposure to MLOps and analytics enablement.