Top Data Jobs in Belfast

Lead insider risk and data loss investigations from triage to closure, operate and tune DLP across environments, build detections and workflows, partner with HR/Legal/Compliance/IT, mature insider risk program, support audits, and mentor others.

Lead design, development, and optimization of high-performance ETL pipelines using Ab Initio for Oracle ledger processing. Collaborate with business and cross-functional teams, drive SDLC within Agile, perform SQL-based data investigations, build automation utilities, monitor/resolve production issues, and manage testing and deployments.

Develop and enhance bespoke Python backend services, collaborate with clients on architecture and design, implement best-practice solutions, use appropriate tools/frameworks, write automated tests, manipulate complex datasets, share knowledge, and work in cross-functional teams to deliver clean, efficient software.

Lead a small senior data engineering team owning the end-to-end data platform: streaming, warehousing, modelling, pipelines, ML lift, and operational excellence. Drive delivery, coach engineers, review technical designs, enforce data contracts and quality, manage costs (FinOps), and partner with Product and leadership to set roadmaps and risk. Build and grow an emerging ML function.

Design, build, and maintain scalable batch and streaming data pipelines, internal tools, and APIs to support analytics, product features, and ML. Collaborate with product and engineering to improve data infrastructure, ensure reliability, testing, and observability in a cloud-native environment.

Lead high-value analytics projects: translate business questions into analysis plans, run exploratory and diagnostic analysis, apply statistical and quasi-experimental methods, evaluate initiatives, quantify impact, and coach analysts while shaping analytical standards across Marketing & Sales.

Lead analytical work to inform high-value decisions: translate business questions into analysis plans, run exploratory and diagnostic analysis, design statistical models, experiments and quasi-experimental methods to quantify impact, and coach analysts while shaping analytics standards and best practice.

Provide second-line oversight of technology, cyber and data risks. Assess risk assessments, test critical controls, challenge first-line teams, inform risk framework evolution, and deliver assurance to senior management to ensure resilient, secure digital services and data protection.

Partner with product and business teams to define metrics, design and analyze experiments, build analytical frameworks, maintain governed dashboards, conduct deep-dive analyses (funnels, retention, cohorts), size opportunities, and connect product metrics to revenue to inform roadmap and leadership decisions.

As a Data Scientist, you will design and deliver bespoke AI solutions, work with clients on project feasibility, and ensure delivery excellence while acting as a technical advisor.

This role involves analyzing complex datasets, developing metrics, building dashboards, and collaborating with teams to enhance fraud detection strategies using ML models.

Design and validate agentic AI capabilities for Protege in PatentSight using ML, NLP, and LLMs. Build retrieval and hybrid search strategies, run experiments, evaluate models, analyze large IP datasets, and translate results into product recommendations while collaborating with engineers, product, and IP experts.

Design, experiment, and validate NLP/LLM and generative AI solutions for patent intelligence. Develop agentic workflows, retrieval strategies (hybrid semantic+lexical), evaluation metrics, and large-scale text processing methods. Partner with product and engineering to translate validated models into scalable, customer-facing features and deliver measurable business impact.

The Data Engineer will build and scale data pipelines, ensure data quality, implement dbt best practices, and empower cross-functional teams with self-service data access.

Perform data profiling and validation across source and target systems during a large-scale public sector data migration. Define and execute data quality rules, test BI dashboards, write and run SQL (MySQL) including stored procedures, document findings, and collaborate with data engineers to remediate issues while championing data quality across accuracy, completeness, consistency, timeliness, validity, and uniqueness.

Lead client-facing data platform architecture and strategy. Design scalable Databricks/Azure or AWS-based solutions, oversee multi-team delivery, incident response, governance, and data security. Mentor engineers, drive roadmap and budget decisions, and ensure resilient, high-quality data pipelines aligned to business goals.

This role involves developing and maintaining kdb+ applications, collaborating with business users, and mentoring junior developers in a dynamic team environment.

The Data Engineer role involves implementing and optimizing SaaS data products, designing integration patterns, and providing technical leadership while collaborating with stakeholders.

As a Senior kdb+ Engineer, you will lead technical delivery, design kdb+ architectures, mentor developers, and drive innovation in high-performance systems.

As a Senior kdb+ Engineer, you'll lead client projects, design kdb+ architectures, mentor developers, and drive technical innovation in high-performance data systems.

Lead the data solutions strategy for PR&C PSP division, managing data initiatives, teams, and collaborating on analytics projects. Ensure compliance, governance, and optimize data services while communicating technical solutions to stakeholders.

Lead mechanical delivery for hyperscale and co-location data centre projects across the UK and EMEA. Drive technical excellence, client relationships, work winning, team leadership, project financials, and represent AECOM in the data centre community.

Lead the API-first developer experience for CME Group's external Data & Analytics distribution. Build high-performance SDKs (Python, C++), public schema registry, documentation, and cloud-native distribution. Act as technical, customer-facing liaison to translate feedback into product requirements, drive versioning, authentication normalization, telemetry, and CI/CD for publishing and governance.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.