Gravitas Recruitment Group (Global) Ltd
Senior Data Architect
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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 Responsibilities
- Own 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).
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Essential Requirements
- Significant 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.
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Desirable
- Databricks 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.
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