Top Data Jobs in Belfast

Design and deliver production-grade AI/ML solutions for Kainos Workday products, including LLM-driven features, model deployment, dashboards, and mentoring junior staff. Collaborate with engineering and clients to improve product functionality, scalability, and efficiency.

Mid-level Python Engineer to learn and implement OneTick solutions, build Python applications and data pipelines, integrate with client platforms, deliver production-ready scalable solutions, troubleshoot production issues, collaborate with stakeholders, and develop domain expertise through training and hands-on delivery. Role is Belfast-based (hybrid) with potential travel to London and New York.

Lead multi-skilled agile teams to design, build and productionise modern data solutions. Own technical architecture, collaborate with infrastructure and customer architects, define functional and non-functional designs, mentor staff, estimate delivery timelines, contribute to data community and support pre-sales technical solutioning.

Design, build, and maintain scalable ETL/ELT pipelines and modern lakehouse architectures. Optimize data solutions using Databricks, Spark, and AWS. Produce high-quality Python code, data models, and monitoring to ensure data accuracy, reliability, and performance. Collaborate with product teams, troubleshoot complex data issues, and improve infrastructure scalability.

Own and operate Databricks production data pipelines for a predictive CRM platform: monitoring, incident response, cost and performance optimization, migrating legacy ETL, onboarding customers, enforcing Delta Lake architecture and multi-tenant isolation, and applying CI/CD, security, and observability best practices to ensure reliable, scalable data delivery.

Design, build, and scale cloud-native data warehouses and robust ETL/ELT pipelines (primarily BigQuery). Optimize performance, implement partitioning and cost controls, ensure data governance, observability, and regulatory reporting support, and collaborate with analytics and engineering stakeholders.

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.

Support data management and governance by managing data assets, ensuring data quality, standards, and policies; publish and protect data for analytics; contribute to analytic platforms and reporting solutions; work on moderately complex projects with general guidance.

Lead needs assessments and stakeholder engagement to design a centralized conservation data system. Advise on technical platform options, collaborate with IT, produce reports and presentations, and drive adoption across portfolios. May lead project teams and support adaptive management through data strategy and implementation.

Lead the design and development of data services, manage data reliability, create data models, and ensure data products support ML workflows.

Consult on data science and advanced analytics projects: translate business needs into analytical approaches, design and build models, run exploratory analysis, deliver end-to-end analytical solutions, collaborate cross-functionally, present findings to technical and non-technical stakeholders, and support handover and implementation.

Lead global market intelligence for Iron Mountain Data Centers by analyzing macro trends, cloud architectures, and power constraints; build GIS-based site selection tools; embed market data into underwriting and financial models; deliver investment recommendations and standardized market frameworks to executive leadership.

Operate, maintain and optimise a pyrolysis plant; build and validate process models (Aspen); perform lab testing and material analysis; support commissioning, safety assessments (HAZOP), MRV systems and scale-up; develop SOPs and train site staff to deliver repeatable carbon-removal operations.

The role involves developing data pipelines, managing metadata and data quality in Azure, ensuring compliance with data governance standards, and collaborating with data teams.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

The Market Data Analyst will oversee data quality and operations for metals and minerals, monitor market trends, support clients, and improve data workflows using SQL and Python.

The role involves developing go-to-market strategies for VAST Data within the UK Defence & Secure Government sectors, building relationships with key stakeholders, identifying and closing strategic sales opportunities, and representing the company at industry events.

Senior Data Scientist owning end-to-end analytical problems: experiment design, predictive and inferential modeling, performance measurement, and cross-functional partnership to improve retail AI products. Duties include data acquisition, modeling, validation, auditing system outputs, building reusable statistical methods, and communicating findings to influence product and operations.

Develop Front Office Trading software focusing on low latency components. Engage in end-to-end development, from design to implementation, mainly using C++.

Lead end-to-end development and productionisation of time-series forecasting ML solutions: design, train, deploy models, build cloud-native data pipelines, collaborate with stakeholders, and monitor model performance to optimise clinic scheduling and staffing.

Lead end-to-end SAP S/4HANA data migration activities: define strategy and governance, manage mapping, cleansing, ETL and reconciliation, execute mock and production loads, resolve defects, coordinate with testing and business teams, and support cutover readiness.

As a Customer Data Solution Architect, you will design secure and scalable customer data solutions, providing thought leadership and ensuring compliance with design principles while collaborating across teams to enhance data strategies and analytics capabilities.

Design, build, and support large-scale data systems and pipelines, ensuring reliability and scalability while collaborating with cross-functional teams to meet data requirements.

Lead design and governance of customer data solutions for retail: identity resolution, MDM, integration, and modern data platforms (lakes/lakehouses). Create design artefacts, enforce design principles, review solutions for compliance, collaborate with stakeholders, and apply industry trends to improve personalization and analytics.

Build and maintain production data pipelines and features in Python; own project lifecycle from design to reliable production; set technical direction for the Insights platform; improve engineering standards (testing, observability, data quality); apply AI across products and pipelines; help establish semantic/AI-ready data layers.