Top Data Jobs in Edinburgh

Monitors and maintains client asset and securities data, validates accuracy against market sources, evaluates data vendors, and supports reference data products. The role responds to data inquiries, documents workflows, performs basic SQL analysis, maintains real-time investment data, ensures risk and control compliance, and analyzes information flows between accounting and custody systems. It also develops expertise in fixed income, equities, corporate bonds, and related investment processes.

Own enterprise technical support cases from triage through resolution across Kubernetes, cloud infrastructure, ML platforms, authentication, data connectivity, and model deployment. Diagnose issues, write actionable Jira bug reports, create knowledge-base documentation, coordinate global case handoffs, and communicate clearly with customers. The role includes live troubleshooting sessions and participation in an EMEA weekend on-call rotation.

Leads technical strategy and pre-sales engagement for hyperscale cloud, AI, and data center networking solutions. Partners with customers, hyperscalers, technology providers, sales teams, and product organizations to co-design architectures, shape go-to-market strategy, and influence product development. Requires deep expertise in routing, switching, SDN, network automation, virtualization, and hyperscale infrastructure, plus strong executive communication, RFP response, and relationship-building skills. Travel of up to 50%, including international travel, is required.

Lead complex cloud, AI, digital transformation, and technology programmes for enterprise, public sector, and regulated-industry customers. Responsibilities include delivery planning, governance, risk management, financial controls, executive stakeholder engagement, presales support, and cross-functional team leadership. The role ensures delivery quality, customer satisfaction, and measurable business outcomes while operating across secure and regulated environments.

Build and execute Cribl’s EMEA go-to-market strategy with global systems integrator partners such as Accenture and Deloitte. Develop partner relationships, create sales pipeline, support joint opportunities, grow partner capabilities through training and enablement, develop repeatable solutions, connect field teams, and manage partnership metrics including pipeline, revenue, and engagement. The role requires regional collaboration across EMEA and occasional travel.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Leads and scales a data engineering team of 8+ engineers, owning data strategy, platform modernization, architecture, reliability, and engineering standards. Partners with product, analytics, and commercial teams to deliver scalable, secure, high-quality data solutions. Responsibilities include coaching, mentoring, roadmap ownership, stakeholder management, performance measurement, and representing data engineering with senior leadership. The role requires technical credibility across cloud platforms, data warehouses, orchestration, modeling, pipelines, infrastructure as code, and CI/CD.

Develop and maintain customer-facing analytical reporting, data pipelines, and data models. Build Python applications, ensure data quality and consistency, collaborate with analytics engineers, and enable business teams to access actionable data. The role also involves cloud data warehouse optimization, infrastructure as code, software engineering best practices, and cross-functional product collaboration within an agile SaaS environment.

Leads research and production development of generative AI and large language model systems for cybersecurity. Responsibilities include defining AI research strategy, developing novel reasoning and summarization approaches, selecting model architectures and deployment strategies, building large-scale production systems, mentoring scientists, establishing evaluation standards, and guiding cross-functional technical initiatives. The role also represents the company through publications, speaking engagements, and technical thought leadership.

Advance analytics and ML solutions for a global pharma client: develop, implement and monitor models; build data models and BI analyses (Spotfire); liaise with stakeholders; improve provisioning and inspection-ready documentation; apply statistical methods to solve business use cases.

Lead multidisciplinary teams delivering complex hyperscale, colocation, and enterprise data centre projects across Europe. Oversee design from site due diligence and campus planning through construction documentation, ensuring technical quality, permitting compliance, risk mitigation, deadlines, and client satisfaction. Manage stakeholder relationships, present project outputs, support commercial governance, and coordinate localized delivery across UK&I and European offices. Regular travel is required.

Manages technology platforms, system configuration, data integrity, access controls, dashboards, integrations, and technical support across JLL and client systems. The role monitors system performance, automates validation and reporting workflows, supports cybersecurity compliance, configures locations and user permissions, coordinates vendors and IT teams, manages equipment and training processes, and leads technology upgrades, change initiatives, and process improvements.

Analyzes financial crime data to produce actionable insights supporting regulatory supervision and financial crime prevention. The role involves interrogating and manipulating data, answering defined questions, presenting findings to technical and non-technical audiences, developing dashboards and analytical approaches, and collaborating with Data and Supervision teams. It requires strong communication, stakeholder management, prioritization, judgement, and the ability to deliver high-quality work under tight deadlines.

Leads UK regulatory compliance and privacy oversight, serving as the Data Protection Officer. Responsibilities include DPIAs, privacy risk assessments, breach governance, data subject rights, compliance monitoring, control reviews, audits, regulatory inquiries, management reporting, issue remediation, and translating requirements into governance standards. Partners with Legal, Product, Engineering, Operations, Risk, and Compliance teams to strengthen the UK compliance framework and oversee consumer protection, conduct risk, and vulnerable customer programs.

Build and maintain scalable data-focused REST APIs, pipelines, and fraud recommendation applications. Develop batch and streaming ingestion using Python, SQL, PostgreSQL, Redis, and optionally PySpark. Deploy services on Kubernetes with KONG and ArgoCD, ensure reliability and data quality, monitor applications, troubleshoot issues, and collaborate with engineers, analysts, data scientists, and product managers in an agile environment.

Owns data quality, reporting, analytics, and deal-management data for a private companies investment team. Builds and improves Power BI dashboards, reconciles investment and financial data across systems, identifies insights and risks, and supports decision-making. The role also manages data models, reporting processes, transaction records, and continuous improvement initiatives across platforms including iLevel and Snowflake. It requires strong stakeholder collaboration, financial data analysis, and practical automation and AI exploration.

Designs, develops, and supports secure cloud-based data integration solutions using Microsoft Fabric and Azure. Responsibilities include client discovery, requirements gathering, ETL and ELT development, REST API and SFTP integrations, data pipeline implementation, production monitoring, incident investigation, and reliability improvements. The role collaborates with architects, analysts, project managers, and delivery teams across multiple client engagements.

Leads flagship AI Labs initiatives from scoping and research through production deployment. Designs and evaluates AI agents and agentic workflows, guides production-grade architecture, establishes quality and safety measurement, and partners with business and engineering stakeholders. Manages and mentors 3–6 AI scientists while communicating technical outcomes to senior leaders and broader audiences.

Supports implementation and operation of data governance frameworks within asset management. Responsibilities include maintaining data dictionaries and glossaries, developing data quality validation rules, reporting governance metrics, identifying and resolving data quality gaps, strengthening controls, coordinating governance forums, and translating data governance requirements for delivery teams. The role partners with data owners, stewards, technology teams, and operational stakeholders to improve data quality and mitigate risk.

The Data Modeller will define conceptual, logical, physical, canonical and semantic data models across business and technology teams. Responsibilities include identifying entities and dependencies, designing data products and contracts, supporting Snowflake or comparable platforms, maintaining modelling standards, integrating metadata and catalogues, mapping source-to-target transformations, and assessing change impacts. The role requires strong SQL, data querying, collaboration, and communication skills to create consistent, reusable and traceable data designs.

Designs and governs scalable data architecture across ingestion, transformation, storage, APIs, events, security, observability, and analytics. Defines reusable platform patterns, reviews technical designs, guides engineering teams, and ensures data solutions are secure, reliable, performant, maintainable, and cost-effective. The role also covers data quality, lineage, integration, technical debt, technology evaluation, and architecture documentation across cloud data platforms, warehouses, and lakehouses.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Design and deliver secure, scalable Azure data platforms for global enterprise customers. Lead architecture engagements, roadmaps, proofs of concept, pilots, and production deployments across Microsoft Fabric, Azure Databricks, databases, governance, and AI workloads. Own technical delivery, workload health, resiliency, security, capacity optimization, and adoption outcomes. Resolve technical blockers, collaborate with product and engineering teams, develop reusable implementation assets, and mentor others while enabling Azure consumption and production-scale AI scenarios.

Leads biomedical data science for clinical and health research, integrating clinical, observational, EHR, genetic, wearable, electrophysiological, and video data. Develops signal-processing methods, machine-learning models, probabilistic and time-series analyses, scalable data pipelines, and reproducible workflows. Validates clinically relevant models, supports disease phenotyping and predictive modeling, ensures compliance with pharmaceutical and healthcare standards, and communicates technical findings to clients and stakeholders.

Provide privacy advisory and compliance consulting across multiple client sectors. Responsibilities include privacy gap analyses, audits, DPIAs, policy development, AI privacy assessments, supplier due diligence, breach response, regulatory communications, data subject rights requests, reporting, training, and stakeholder advice. The role requires translating privacy risks into practical business decisions while collaborating with legal, information security, and operational teams.