Top Data Analyst Jobs in Belfast

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.

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.

The Data Analyst develops and maintains Power BI dashboards, datasets, data models, SQL and DAX solutions, and data pipelines. The role supports AWS cloud analytics integration, data quality, troubleshooting, governance, documentation, and workspace administration. It coordinates data engineers, translates business requirements into technical deliverables, collaborates with stakeholders, and communicates findings to nontechnical audiences while supporting agile delivery and data privacy compliance.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Own analytics across the participant lifecycle, including acquisition, onboarding, activation, engagement, retention, churn, and reactivation. Build metrics, dashboards, reporting frameworks, and experimentation analyses using SQL and Python. Partner with Product, Operations, Growth, Data Science, Commercial, and Finance to identify marketplace opportunities, evaluate experiments, and translate participant and supply data into actionable commercial and strategic decisions.

Build and enhance AWS QuickSight reporting for Customer Service, create reusable datasets, integrate business data sources, and establish consistent metrics and documentation. The role translates stakeholder needs into dashboards, automates manual reporting, validates data quality, investigates issues, and supports self-service analytics and knowledge transfer during a six-month engagement.

Develops advanced analytics solutions to address business challenges, improve processes, and generate customer and commercial value. Works with stakeholders to define analytical questions, create visualizations, communicate insights, and deliver data-led recommendations. Collaborates within Agile, multidisciplinary teams alongside data scientists and engineers. Requires SQL, visualization, data architecture, and stakeholder communication skills; Python and Apache Airflow are advantageous.

Analyze complex datasets, develop dashboards and reports, translate stakeholder requirements into data-driven solutions, and support analytical models and AI-enabled capabilities. The role involves collaborating with engineers and multidisciplinary Agile teams, ensuring data quality and documentation, presenting insights, and supporting UX/UI design within a secure Defence programme.

Lead development and enhancement of Citi's trade cost analytics platform. Design trade and cost analytics, reconciliation processes, and fee calculations. Partner with front/middle office, operations, and technology to gather requirements, translate business needs into SDLC deliverables, and deliver reporting and platform improvements to increase transparency and accuracy.

Analyze fraud and scam data to identify trends, patterns, risks, and potential issues. Develop, test, deploy, and improve fraud reporting and provide actionable insights to prevent financial loss. Collaborate with analytics teams, business stakeholders, and regulators on reporting requirements and ad hoc analyses. Communicate technical findings clearly to non-technical audiences while maintaining accuracy and attention to detail.

Analyze Gecko browser engine telemetry across Desktop and Android, build leadership dashboards, identify telemetry gaps, develop frameworks to remove bot and hardware noise, and correlate performance metrics with user behavior. The role requires advanced SQL, statistical analysis, data visualization, browser component knowledge, and independent problem solving to translate engineering data into product strategy.

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.

Analyze customer, market, and operational data to identify trends, risks, and opportunities. Produce reports, dashboards, forecasts, and recommendations for senior stakeholders. Use SQL, SAS, SAS Viya, and modern data tools to manage complex datasets, improve data quality, automate workflows, and support strategic decisions. Collaborate across business, data, and technology teams to improve processes and embed data-led decision-making.

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.

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.

Collect, clean, validate, and analyze data using Excel, SQL, Power BI, and Microsoft Fabric. Create dashboards, reports, visualizations, KPI reporting, and actionable recommendations for business and client decision-making. Collaborate with analysts, consultants, and stakeholders, present findings clearly, maintain reporting solutions, and support data quality and project delivery. The role offers early-career development in data analytics and consulting.

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.

Embedded within the commercial team, the Senior Data Analyst will own core sales and revenue metrics, improve pipeline and forecast accuracy, investigate CRM data quality, size commercial opportunities, and analyze partner, retention, and renewal performance. The role translates ambiguous business questions into actionable recommendations, defines trusted metric frameworks, communicates insights to senior stakeholders, and increases self-service analytics adoption across non-technical commercial teams.

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.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

The role involves programming and data review for real-world data analysis, supporting epidemiologists, and managing complex data sets using statistical programming languages and tools.

Use SQL and Python to analyse transaction monitoring and fraud rule performance, identify patterns and anomalies, reduce false positives, and prioritise high-risk cases. Partner with FinCrime, Product, Compliance and Data teams to improve controls, data pipelines and detection logic, support scoring and future ML use cases, and translate analysis into actionable recommendations that balance fraud prevention with customer friction.

Lead marketing measurement: own attribution, incrementality testing, and media mix modeling. Design and analyze experiments, build repeatable templates and self-serve analytics, translate results into budget and growth recommendations, ensure data integrity, and embed AI tools into analysis workflows to measure pipeline and revenue impact.