Top Data Jobs in Belfast

Lead data architecture and strategy across OLTP, OLAP, and AI systems. Drive AI-first foundations (LLM orchestration, RAG, real-time inference), ensure DataOps/CI-CD, mentor technical leads, run architectural reviews, partner with product and engineering leadership, and optimise platform security, observability and costs.

Lead delivery of advanced AI solutions, provide technical and architectural leadership, drive adoption of cloud-native AI engineering, and manage, coach, and develop a multidisciplinary data science team while ensuring responsible AI practices and strong stakeholder engagement.

Develop, fine-tune, evaluate, and productionise ML and LLM models for customer feedback tasks (extraction, retrieval, reranking, summarisation, sentiment). Build retrieval and embedding pipelines, contribute to evaluation frameworks and metrics, write tested code, collaborate on integrations and monitoring, and translate product needs into ML experiments while keeping up with research.

Lead or contribute to statistical programming for clinical trials, focusing on SDTM/ADaM datasets and TLFs. Oversee quality, validation, and dataset specifications, communicate with sponsors, and provide guidance on programming requirements. Oncology experience and team leadership are advantageous.

Manage clinical data activities for trials: design CRFs and databases, program/test edit checks, perform coding (MedDRA/WHO‑Drug), export CDISC SDTM datasets, generate queries, coordinate data entry and DB developers, support database lock and sponsor communication.

The role involves owning product feature development, participating in system design, and maintaining software performance in an agile setting.

The Data Mentor provides technical support and feedback to apprentices, ensuring high standards in teaching, learning, assessment, and learner progression monitoring.

As an Energy Consultant, you'll bridge Gorilla's SaaS solutions with energy market needs, drive pre-sales engagements, and support deal strategies through workshops and tailored presentations.

Measure and optimize underwriting using statistical analysis and machine learning on claims, risk signals, and underwriting data. Build models for risk assessment, pricing, and automation; create dashboards and reports; collaborate with actuarial, product, and engineering teams; lead initiatives and mentor team members to improve underwriting efficiency and risk selection.

The Director Analyst focuses on data integration and engineering, providing insights, advice, and research to help organizations improve their data practices and strategies.

The Data Engineer will design and support data warehouses, create analytics dashboards, perform data quality analysis, and identify process improvements. Responsibilities include collaborating with stakeholders to develop insights and ensure data governance.

Lead the Finance & Regulatory Data team, overseeing finance data strategy, governance, and analytics to support corporate finance and audits.

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 ownership of private markets data model and architecture, manage integration/connector inventories, design data migration and integration frameworks, advise clients and support sales, and bridge advisory and technical delivery teams to enable BI and enterprise performance solutions.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Lead mechanical engineering projects for data centre design and delivery, collaborating with multi-disciplinary teams and contributing to strategic growth.

Design, build, and maintain scalable analytics models and automated reporting. Partner with Sales, Product, Marketing, and Finance to define KPIs, deliver ad hoc analysis, improve data quality and observability, and establish analytics engineering best practices to enable self-service analytics.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.

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 data strategy and standards across product teams, develop experimentation best practices, mentor data scientists and analytics engineers, collaborate with product/engineering/design/research, and apply advanced data techniques to improve user engagement and product decision-making.

The Forward Deployed Data Solution Engineer works embedded within teams to ensure software quality, guide technical decisions, and design integration patterns, focusing on AI-enabled capabilities and data governance.

The Senior Data Scientist will develop and test deep learning architectures, drive strategy across teams, and ensure models effectively solve real-world financial problems while mentoring others.

Manage the full commercial lifecycle for enterprise and strategic customer accounts: renewals, pricing, contract amendments, upsell strategy, and expansion. Build bespoke commercial strategies using usage data and market context, forecast renewal pipeline, lead commercial QBRs, negotiate with senior stakeholders and procurement, and partner with Customer Success and solution consultants to quantify ROI and drive retained and expanded ARR.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.