Top Data Jobs in Belfast

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.

Analyze complex capital and related data for financial markets, delivering insights, visualizations, and recommendations to product desks and business partners. Identify trends, optimization opportunities, data-quality issues, and process improvements across multiple platforms. Collaborate with stakeholders and Technology to resolve complex requirements and systems issues, while communicating findings clearly and supporting capital-management initiatives.

Lead the design and development of data services, manage data reliability, create data models, and ensure data products support ML workflows.

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.

Graduate developer role with a three-month Belfast training program focused on Q programming and the kdb+ time-series database. Responsibilities include learning to capture, store, analyze, and visualize financial data, followed by potential consulting and support work with investment banks and hedge funds internationally. Candidates must hold a qualifying STEM degree, have coding experience, communicate well, solve problems collaboratively, relocate to a global hub after training, and have UK work authorization.

Build and enhance dashboards and counterparty credit risk exposure tools for crisis management, innovation, and regulatory initiatives. Analyze counterparty credit risk and XVA Trading issues, collaborate with trading, risk, operations, and technology stakeholders, and manage time-sensitive projects. Identify opportunities to incorporate AI-driven innovations into analytical tools and processes. Requires advanced SQL and Tableau, strong quantitative and analytical skills, and ideally derivatives modeling knowledge.

Leads Grant Thornton’s internal AI product strategy, portfolio governance, roadmap, delivery oversight, adoption, and continuous improvement. The role translates senior leadership priorities into governed, scalable AI products, accelerators, and workflow tools. Responsibilities include leading multidisciplinary teams, managing stakeholders, evaluating build-versus-buy decisions, overseeing risks and investment, supporting responsible AI practices, developing reusable intellectual property, and coaching team members. The position is hybrid, typically requiring two days weekly in the Dublin or Belfast office.

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.

Analyze and manage reference data products for a global corporate actions platform. Define business and functional requirements, data models, mappings, user stories, and product backlogs. Partner with technology, operations, vendors, and stakeholders to develop interfaces, validate data, publish information downstream, and improve governance, automation, and data quality. Perform SQL-based analysis, documentation, user training, process streamlining, and support AI-ready data initiatives.

Leads product management for a global corporate actions reference-data platform. Responsibilities include defining requirements, epics, user stories, and backlog priorities; data modeling, vendor mapping, profiling, transformation, and SQL validation; API and web interface strategy; vendor engagement; golden-copy governance; automation and AI-ready data initiatives; stakeholder management; roadmap delivery; training; and release governance.

Leads architectural design and coordination for complex multidisciplinary data centre and infrastructure projects through all RIBA stages. Responsibilities include managing design teams, reviewing technical documentation, ensuring regulatory and quality compliance, coordinating vendors and disciplines, presenting to clients, mentoring staff, supporting bids, managing budgets and resources, and overseeing design delivery against demanding deadlines. The role requires an ARB-registered architect with strong technical design, design management, digital workflow, and multidisciplinary project experience.

Lead architectural design and technical delivery for large multidisciplinary data centre projects across Europe. Coordinate architectural and engineering teams, oversee design documentation, maintain technical quality, manage deadlines, support site design interfaces, present to clients, and ensure compliance with UK standards and CDM safety principles. The role also involves team coordination, resource and training support, digital workflow improvements, and use of Revit-based 3D modelling and common data environments.

Supports Deutsche Bank’s global Market Data Services team by analyzing market data usage and costs, identifying cost-reduction opportunities, reporting requirements and metrics, supporting vendor relationships and contract negotiations, managing vendor notifications, and overseeing application risk, compliance, and annual recertification. The role works with business managers, application owners, vendors, sourcing, and infrastructure teams.

Monitor and analyze financial news, market data, company disclosures, ratings changes, deal terms, redemptions, and maturities. Maintain accurate investor relations details, reporting dates, datasets, and client-facing updates. Use HTML and proprietary tools to streamline publishing and data workflows. The role requires fast, accurate decision-making, strong communication, attention to detail, prioritization, and an interest in financial markets. Work follows rotating EU and US shifts.

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.