Top Data Jobs in Belfast

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.

Manage client relationships as a subject matter expert, collaborating with Account Executives to drive revenue, engage clients, and provide product insights for innovative solutions.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Design, develop, and deploy machine learning and LLM-based solutions for risk scoring, compliance prediction, churn analysis, and contractor analytics. Integrate models into production on AWS and Azure, use Microsoft Fabric for data pipelines and feature engineering, implement model monitoring and retraining, and collaborate cross-functionally within an Agile SDLC.

Client-facing Principal Data Engineer leading design and delivery of enterprise Databricks-based data platforms. Provide architecture leadership, mentor engineering teams, drive platform optimisation, define standards, support technical governance, and deliver across multiple consultancy engagements.

Lead design and implementation of data governance and MDM strategies, develop policies and metadata/lineage practices, enforce data quality, deploy governance tooling, engage stakeholders, ensure regulatory compliance, and mentor team members.

Design, build, and maintain scalable cloud-based data platform and ETL pipelines on Azure. Develop data models, ensure data quality, optimize performance, implement governance and security, and collaborate with stakeholders and data scientists to enable data-driven solutions.

Translate business needs into technical solutions by collecting, cleaning, and analysing data from multiple sources; build and maintain dashboards and reports; use SQL and Python to automate data processes; ensure data quality; present findings to stakeholders and collaborate across teams to drive process improvements.

Lead and define the data science and AI strategy, deliver production-grade ML and generative AI solutions, operationalise models with MLOps and governance, build and mentor a high-performing team, and influence stakeholders to drive measurable business impact.

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.

As a Senior Data Scientist, you'll develop AI solutions with machine learning, mentor others, and ensure responsible AI practices while collaborating with clients to solve business challenges.

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.

As a Data Entry Specialist at Iron Mountain, you will be part of a team that focuses on records management, digital transformation, and customer service. You will help in maintaining data accuracy and contribute to innovative solutions.

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.

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.

The Account Manager for Data Services will generate business opportunities, manage complex sales cycles, and nurture key relationships, particularly within regulated industries. This role involves collaboration with internal teams and the provision of ongoing client support post-sale.

Build and deliver internal data tools and platforms, support ingestion systems and promote operational excellence in a collaborative environment.

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.

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

Lead and support analytics lifecycle activities: manage analytic data platforms, govern data access, design and implement reporting/BI, apply advanced quantitative modeling, deliver actionable business insights, contribute to policies, work independently on complex projects and mentor junior colleagues.

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

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.

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.