Top Data Jobs in Belfast

Build and scale governed data products, pipelines, analytical models, semantic layers, APIs, and AI-enabled interfaces. Establish standards for data modeling, orchestration, testing, observability, CI/CD, security, and lifecycle management. Partner with stakeholders to define data contracts and product roadmaps, deliver solutions end to end, improve analytics governance, and mentor colleagues. The role requires strong data and analytics engineering expertise, product judgment, and practical experience directing AI coding agents.

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.

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.

Leads the end-to-end design of data solutions, including ingestion, transformation, data modeling, and cloud data platform architecture. Defines target-state solutions using Databricks, Azure, and AWS across data warehouses, lakes, and lakehouses. Designs data product architectures, ownership frameworks, and solutions supporting AI and analytics. Collaborates with architects, engineers, platform owners, and analysts while documenting and presenting complex solutions to senior and non-technical stakeholders in regulated environments.

Develop measurement frameworks for offline and out-of-home marketing campaigns, including geo holdout tests, matched-market tests, media mix modeling, and incrementality studies. Combine offline spending with digital and product signals to assess marketing effectiveness. Partner with Marketing leadership and Growth Data scientists to select test markets and channels, size investments, align online and offline measurement, and communicate uncertainty clearly.

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.

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.

Own the company’s end-to-end data platform, including ingestion, S3 data lakes, ClickHouse, dbt transformations, orchestration, and BI/CRM data delivery. Improve reliability, historical accuracy, cost, and metric governance while defining and defending business KPIs. Partner with Customer Success, Sales, Product, and leadership to translate business questions into durable metrics and establish data standards. This is a senior individual contributor role focused on hands-on engineering, analytical rigor, and stakeholder communication.

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.

Lead data integration activities for Kinaxis solution deployments, including data mapping, transformation, loading, testing, validation, system configuration, and deployment. Design integration solutions, define requirements, support customer workshops and training, and collaborate with architects, support, and cloud teams. Advise customers on integrating Kinaxis Maestro with enterprise systems using ETL tools, APIs, databases, and ERP connections. The role is remote in the UK and may require up to 70% travel.

Own analytics across the participant lifecycle to support acquisition, onboarding, activation, engagement, quality, retention and reactivation. Build metrics, dashboards, and experimentation frameworks with SQL and Python; partner with Product, Operations, Growth, and Data Science to run experiments and translate marketplace data into actionable decisions that improve participant health and supply sustainability.

Leads UK and Ireland strategy for Customer Data Management, using customer, market, regulatory, competitive and commercial insights to define priorities. Shapes propositions, positioning, packaging and business cases; translates customer needs into product, data, technology and operational requirements; leads cross-functional initiatives; measures customer value; and supports Sales, Pre-Sales and Marketing with value propositions and market narratives.

Leads strategically important data science initiatives across complex business domains. Shapes data strategy, develops measurement frameworks, applies experimentation, causal inference, forecasting, optimization, and decision science, and partners with senior leaders to drive measurable outcomes. Remains hands-on with complex analyses, experiments, models, and prototypes while establishing technical standards, governance, reproducibility, and documentation. Coaches data scientists and analytics engineers and stewards critical data products end to end.

Lead product-focused data science work: run quantitative analyses and large-scale A/B tests, enable product teams with measurement, drive lifetime value analysis with finance, and partner with engineers to ensure correct data collection and actionable insights.

Lead the architecture and evolution of a Snowflake-based operational data platform. Design secure, governed, scalable data warehouse solutions, real-time ingestion, API integrations, AI-enabled capabilities, and natural-language querying interfaces. Define data flows, schemas, roadmaps, architectural standards, and governance while collaborating with engineering, data, business, and executive stakeholders. Troubleshoot complex platform issues, guide technical direction, and promote modern data engineering practices across enterprise systems.

Leads architecture and evolution of Snowflake-based operational data platforms, including real-time ingestion, AI-enabled capabilities, API integrations, data modeling, governance, and secure enterprise data flows. Partners with engineering, data, and business stakeholders to define roadmaps, standards, and technical direction while troubleshooting complex systems and communicating architecture decisions to technical and executive audiences.