Top Data Jobs in Belfast

Supports the enterprise data governance program by developing policies, enabling data ownership and stewardship, governing metadata and data quality, coordinating compliance activities, facilitating stakeholder engagement, tracking governance initiatives, and reporting KPIs. The role promotes adoption of data catalogs, business glossaries, data standards, privacy requirements, retention controls, and governance best practices across business and technology teams.

Own enterprise customer programs from contract signature through expansion, leading delivery teams, milestones, stakeholder communication, adoption, and change management. Partner with sales and customer success to scope engagements, identify expansion opportunities, and translate executive goals into executable AI implementation plans. Serve as the customer advocate internally while guiding solutioning across model development, deployment, governance, and enterprise data science workflows.

Supports Finance and Go-To-Market departments by designing data recording systems, monitoring data quality, enforcing governance, analyzing large datasets, producing concise reports, and recommending process improvements. The role translates complex findings into actionable insights for non-technical stakeholders and supports Sales, Marketing, and Customer Success objectives.

Lead a team of 10 Data Security Specialist Account Executives across EMEA and APJ. Responsibilities include recruiting and coaching sales talent, managing regional business plans and forecasts, collaborating with sales, marketing, product, services, and partners, and driving revenue attainment. The role requires software or security sales experience, data security leadership, regional management, C-level selling, and familiarity with AI/ML technologies.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Analyze large-scale security telemetry, threat intelligence, endpoint, and detection data to identify trends, anomalies, and emerging threats. Build dashboards, reports, data pipelines, and KPI frameworks using SQL, Python, LogScale, or similar tools. Collaborate with data engineering, product, and engineering teams to ensure data quality and translate complex findings into actionable insights for technical and non-technical stakeholders.

Lead B2B product marketing strategy for DataCamp’s data and AI SaaS offerings. Responsibilities include developing positioning and messaging, executing go-to-market campaigns, creating sales and marketing collateral, gathering customer insights, managing analyst relations, and conducting competitive analysis. The role partners closely with sales, customer success, product, and content teams to drive revenue, adoption, and market impact.

Design and deploy production LLM-backed agentic systems for financial-services clients. Build tool-using agents, MCP servers, retrieval and multi-agent orchestration, evaluations, and guardrails across cloud and locally hosted models. Translate client problems into maintainable proofs of concept, explain technical decisions to varied audiences, and create reusable accelerators. Collaborate directly with client engineers and stakeholders while applying strong software engineering, communication, and independent problem-solving skills.

Supports enterprise data governance and risk management across Citi by monitoring data issues, ownership, metrics, controls, findings, and corrective action plans. Coordinates with business, technology, regional governance, and risk teams; prepares regulatory and governance reporting; contributes to control framework assessments; and recommends improvements to data governance policies, standards, procedures, and risk taxonomies.

Provides administrative and operational support for the Phoenix implementation, including data cleansing, migration, testing, validation, and issue tracking. After implementation, manages Bill of Materials uploads and maintenance in Sage X3, ensuring accurate product data, routings, change control, documentation, and data governance across manufacturing and business functions.

Graduate developers complete a three-month training program in Belfast covering Q programming and the kdb+ time-series database. They then work on financial data solutions for investment banks and hedge funds, potentially in global hubs including London, New York, Hong Kong, Singapore, and Toronto. The role requires a STEM degree, strong communication and problem-solving skills, teamwork, attention to detail, and willingness to relocate. Coding experience is beneficial but not required.

Graduate developer role featuring a three-month Belfast training program in Q programming and kdb+ time-series technology. Graduates will develop skills for financial data solutions supporting investment banks and hedge funds, with potential relocation to global financial hubs. Candidates need a STEM bachelor’s degree, strong communication and problem-solving abilities, teamwork, attention to detail, and willingness to relocate. Coding experience is beneficial but not required.

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.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Leads technical delivery of high-performance kdb+ solutions for financial institutions. Designs scalable architectures for billions of time-series data rows, collaborates with quants and traders, mentors developers, and owns application development, testing, support, and maintenance. Drives innovation across kdb+, q, and related technologies while translating business needs into performant code.

Leads advanced data analysis, develops dashboards, KPIs, and analytical models, and translates business problems into data-driven solutions. Works with complex datasets using Databricks, SQL, Python, BI tools, and cloud data platforms. Partners with engineering and governance teams, promotes analytics standards, mentors analysts, and communicates insights to stakeholders. Supports strategic decisions through descriptive, predictive, and prescriptive analytics.

Design, build, deploy, and optimize scalable AI and machine learning systems using large datasets. Develop predictive models, recommendation systems, personalization engines, forecasting solutions, generative AI applications, and production ML pipelines. Collaborate with data, backend, and product teams to integrate models into applications, while monitoring performance, data quality, drift, reliability, and cost. Establish best practices for evaluation, experimentation, reproducibility, and deployment, and research emerging AI technologies.

Analyze campaign and CRM data using SQL and BigQuery, reconcile data sources, investigate discrepancies, and build accurate Power BI dashboards. Present actionable marketing insights and recommendations to stakeholders, explain methodology and limitations, defend findings, and independently make routine analytical decisions while escalating significant blockers.

Leads the development of self-service data and AI platforms, analytical frameworks, AI-enabled workflows, and scalable data products. Combines on-chain and off-chain data to answer complex product and business questions, build trusted metrics, identify trends and risks, and support decision-making. Requires expert Dune and SQL skills, deep DeFi knowledge, and hands-on experience with Python, ClickHouse, Airflow, data engineering, and AI-enabled analytics.

Own production Python data pipelines, ETL/ELT workflows, and the ontology powering an AI platform. Integrate warehouses and business applications with graph databases and vector stores, while managing deployment tooling, cloud infrastructure, monitoring, and security. The role begins as hands-on individual contribution and develops toward technical leadership through mentoring and architecture ownership.

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.

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

Develop and maintain data pipelines, models, ETL workflows, validation processes, and interfaces for defence modelling and simulation data. Transform complex simulation outputs into reliable datasets for experimentation, analysis, visualisation, and capability assessment. Collaborate with modelling and simulation engineers, software engineers, analysts, and domain specialists. The role requires Python, SQL, data-quality practices, and the ability to work in offline or restricted environments supporting UK Ministry of Defence projects.

Develop and maintain data pipelines, models, ETL workflows, and validation processes for defence modelling and simulation data. Integrate simulation and analytical environments, automate repeatable processing, and make complex datasets accessible for experimentation, analysis, and visualisation. The role requires Python, SQL, data modelling, and experience working in offline or restricted environments, supporting UK Ministry of Defence projects.