Top Data Jobs in Belfast

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.

Build and maintain FinOps data pipelines, BigQuery and dbt models, cost attribution systems, forecasting and anomaly detection models, and cost-versus-revenue analytics. Identify and implement AWS and GCP savings opportunities, automate governance with Python, Terraform, and Lambda, and partner with Engineering, Finance, Product, and leadership on cloud costs, forecasting, reporting, and architecture decisions.

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.

Provides data centre support on the afternoon shift, covering an existing vacancy. The role supports Iron Mountain’s data centre operations within its broader information management and digital infrastructure services.

Build end-to-end data applications, APIs, internal tools, and user interfaces using AI-assisted development. Work across Python backends, React frontends, data models, Databricks, dbt, pipelines, cloud infrastructure, testing, security, and performance. Review AI-generated code, establish guardrails, improve engineering workflows, and help shape application architecture and technical direction.

Own the strategy, roadmap, governance, delivery, and lifecycle of a Premium data product within a Finance Transformation program. Lead discovery across insurance and finance data flows, align definitions and quality standards, manage cross-functional teams and dependencies, and drive adoption of trusted, reusable data for reporting and decision-making.

Supports data centre clients across Asia-Pacific on public policy, regulation, politics, and commercial strategy. Responsibilities include researching complex policy challenges, developing strategic recommendations, drafting policy positions, managing projects and teams, advising senior stakeholders, identifying business opportunities, and contributing to business development. The role requires strong knowledge of data centre policy issues such as grid connections, permitting, water, sustainability, cybersecurity, resilience, and community relations.

Build, scale, and operate Databricks and AWS infrastructure supporting automated, reproducible machine learning workflows. The role includes infrastructure-as-code with Terraform or Pulumi, containerized platforms using Docker and Kubernetes, system architecture, reliability and cost optimization, and cross-functional collaboration with data and ML teams. The engineer will lead complex projects, improve platform scalability and usability, document systems, and mentor peers while operating production-scale data and ML platforms.

Own the strategy and implementation of CME Group’s external data and analytics API ecosystem. Build Python and C++ SDKs, schema registries, technical documentation, cloud distribution frameworks, authentication, telemetry, CI/CD workflows, and unified API standards. Partner with customers, product teams, engineering, and business stakeholders to improve developer experience, simplify data consumption, and normalize API design across the organization. The role combines hands-on software development, customer integration, technical writing, and enterprise API strategy.

Build and deploy end-to-end data science and AI solutions, including scalable data pipelines, machine learning and generative AI workflows. Translate product and business questions into measurable analytics use cases, analyze product data, establish evaluation and monitoring practices, and collaborate with product, engineering, and analytics teams to deliver business impact.

Leads complex sustainability data analysis for client decision-making, regulatory compliance, and reporting. Responsibilities include data collection, cleansing, validation, transformation, calculations, methodology development, quality assurance, audit trails, dashboards, and client presentations. The role focuses on EPR, PPWR, and sustainability regulations while providing technical leadership, mentoring, project oversight, and business development support.

Leads the design, development, testing, integration, and optimization of scalable data-processing and persistence components. Establishes engineering and operational standards, ensures pipeline performance and compliance, troubleshoots systems, supports proposals, and collaborates with architects, operations, security teams, customers, and managers. Coaches and develops engineers while overseeing code quality, data models, testing, deployment readiness, and technical delivery.

Leads research and advisory work for CIOs on data, analytics, and AI strategy, governance, operating models, architecture, value realization, and emerging technologies. Develops thought leadership, market analysis, presentations, and actionable client guidance; evaluates agentic and composite AI, modern data platforms, AI-ready data, organizational maturity, and capability-building needs. Represents Gartner at client meetings and conferences, supports sales, mentors colleagues, and shapes research agendas.

The Senior Marketing Data Scientist will measure and optimize marketing performance using marketing mix modeling, attribution, customer lifetime value analysis, experimentation, and causal inference. Responsibilities include building scalable data pipelines, automating model deployment and monitoring, creating dashboards, analyzing campaigns, and communicating insights to executives. The role requires strong Python and SQL skills, experience with open-source marketing mix models, marketing analytics expertise, and the ability to lead projects independently.

Design, develop, and support scalable cloud-based data solutions across AWS and Azure. Build ETL/ELT pipelines, data integrations, migration processes, warehouses, data lakes, and lakehouses. Perform data profiling, quality assessments, validation, reconciliation, troubleshooting, and root-cause analysis. Create source-to-target mappings and technical documentation while supporting data governance, security, and compliance. Collaborate with technical and business stakeholders to deliver secure, high-quality data solutions.

Lead Monzo’s EU Data team and shape expansion strategy across European markets. Own data strategy, measurement foundations, experimentation, forecasting, goal setting, and product-market-fit analysis. Represent Data at executive level, influence commercial and product decisions, build cross-business learning loops, and develop a high-performing full-stack Data organization of individual contributors and managers.

Own finance-focused data science and analysis, including revenue and ARR reconciliation, cohort economics, pricing experiments, forecasting, and scenario modeling. Partner with Analytics Engineering to maintain certified finance KPIs and ensure data quality across billing and revenue systems. Translate ambiguous questions from FP&A, RevOps, and leadership into reusable analyses that support planning, board reporting, pricing, and IPO readiness.

Lead the design, development, and operation of scalable data pipelines using Databricks and Azure Synapse. Administer Azure data platform services, Databricks workspaces, security controls, networking, and governance. Manage infrastructure as code with Pulumi or similar tools, build CI/CD automation, monitor platform health, resolve incidents, and mentor junior colleagues while maintaining secure and reliable cloud data environments.

Provides privacy and data protection consulting to multiple clients, covering privacy audits, gap analyses, DPIAs, policy development, AI privacy assessments, supplier due diligence, breach response, regulatory communications, data subject requests, training, and risk reporting. Advises business, legal, and information security stakeholders across varied sectors while managing client engagements and a small consulting team.

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

Lead the design, deployment, and operation of scalable data pipelines and cloud infrastructure for Kpler’s marine insurance initiative. Build containerized AWS services using Python, Docker, Kubernetes, Airflow, and Terraform; manage PostgreSQL and Kafka/Flink streaming systems; establish observability standards; provide technical direction; collaborate cross-functionally; and mentor engineers.

Lead data-driven digital transformation solutions for large capital construction projects. Responsibilities include understanding client problems, advising on best practices, directing technical teams, mentoring junior staff, developing Azure, Fabric, Power BI, and Python solutions, productizing client solutions, and improving internal data processes. The role requires strong communication, analytical thinking, construction or engineering experience, and the ability to translate complex concepts for varied audiences.

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.

Manage customer data migrations and onboarding from initial handoff through completion. Responsibilities include mapping, analyzing, transforming, and importing complex datasets; coordinating with customers, engineers, and internal stakeholders; maintaining accurate records; resolving issues; and improving the onboarding experience. The role requires extensive Excel and database work, customer communication, project coordination, and management of multiple migrations simultaneously.

Build and launch scalable data pipelines, products, APIs, and tools for proprietary market research. Develop big data processing systems, reusable software components, AI-ready data assets, cloud infrastructure, and governance controls. Partner with investment professionals, researchers, data scientists, and Compliance to deliver reliable, auditable, compliant solutions while optimizing system performance, cost, and reliability.