SANS Consulting Services, Inc.

Head of Data & AI Platforms & Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Head of Data & AI Platforms & Engineer in London, with a contract length of C2H and a competitive pay rate. Key skills required include leadership in data engineering, data governance, and experience with Databricks and AI platforms.
🌎 - Country
United Kingdom
πŸ’± - Currency
Β£ GBP
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
April 23, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Data Governance #Data Engineering #Scala #Data Management #Metadata #AI (Artificial Intelligence) #Databricks #BI (Business Intelligence) #Leadership #Security #Monitoring #Data Quality #"ETL (Extract #Transform #Load)" #Data Layers #Data Architecture #Strategy #Compliance #Observability
Role description
Job Title - Head of Data & AI Platforms & Engineer Location - UK (London) Duration - C2H Role Purpose: The Head of Data & AI Platforms & Engineering is accountable for the strategy, delivery, and day-to-day operation of the organisation’s data and AI platforms. The role ensures that data platforms are secure, reliable, scalable, and fit for both business intelligence and advanced analytics and AI use cases. This role owns both change (transformation and enhancement) and run (BAU operations) across data platforms, leading internal and vendor teams to deliver high-quality data services. Key Responsibilities Strategy & Roadmap β€’ Own the roadmap for data and AI platform transformation, including data hub, analytics and consumption platforms. β€’ Introduce new platform capabilities and integrate strategic data sources in line with enterprise priorities. β€’ Define and own data platform architecture, design patterns, and engineering standards. Platform Engineering & Architecture β€’ Lead the implementation of data architecture and data engineering frameworks across ingestion, data layers, semantic layers, and consumption. β€’ Own policies and standards for data platforms, including Databricks, integration, data management, and access controls. β€’ Ensure platforms are designed for performance, scalability, reliability, and security. Data Governance, Quality & Compliance β€’ Implement frameworks for data quality, lineage, observability, and metadata management. β€’ Ensure compliance with security, privacy, and regulatory requirements across all data platforms. β€’ Oversee remediation of data quality issues within BAU operations. Change & Delivery β€’ Accountable for delivery of data platform change initiatives aligned with enterprise prioritisation and release management processes. β€’ Manage delivery of new components, pipelines, and platform enhancements. β€’ Lead and coordinate change delivery teams, including third-party vendors. Run / Business-as-Usual Operations β€’ Own the BAU operation of data and consumption platforms, ensuring availability and performance. β€’ Define, maintain, and report against SLAs and OLAs. β€’ Oversee operational monitoring, incident management, defect resolution, and performance optimisation. β€’ Ensure smooth user onboarding and ongoing platform support. Leadership & Team Management β€’ Build and lead high-performing data engineering, platform, and data management teams. β€’ Establish in-house BAU capability across engineering, data quality, and platform operations. β€’ Manage vendor partners to ensure effective delivery and value for money. Key Skills & Experience β€’ Senior leadership experience in data platform and data engineering roles. β€’ Strong knowledge of modern data platforms, analytics, and AI enablement architectures. β€’ Proven experience delivering large-scale data platform change and running enterprise data platforms. β€’ Strong understanding of data governance, data quality, security, and compliance. β€’ Experience managing multi-disciplinary teams and third-party suppliers. Outcomes of the Role β€’ Reliable, secure, and high-performing data and AI platforms. β€’ Clear standards and governance across data engineering and platform services. β€’ Effective balance between transformation delivery and stable BAU operations. β€’ Data platforms that enable analytics, AI, and business decision-making at scale. Thanks And Regards, Kiran Agrawal