Top Data Jobs in Belfast

Lead data integration activities for Kinaxis solution deployments, including data mapping, transformation, loading, testing, validation, system configuration, and deployment. Design integration solutions, define requirements, support customer workshops and training, and collaborate with architects, support, and cloud teams. Advise customers on integrating Kinaxis Maestro with enterprise systems using ETL tools, APIs, databases, and ERP connections. The role is remote in the UK and may require up to 70% travel.

Leads UK and Ireland strategy for Customer Data Management, using customer, market, regulatory, competitive and commercial insights to define priorities. Shapes propositions, positioning, packaging and business cases; translates customer needs into product, data, technology and operational requirements; leads cross-functional initiatives; measures customer value; and supports Sales, Pre-Sales and Marketing with value propositions and market narratives.

Leads strategically important data science initiatives across complex business domains. Shapes data strategy, develops measurement frameworks, applies experimentation, causal inference, forecasting, optimization, and decision science, and partners with senior leaders to drive measurable outcomes. Remains hands-on with complex analyses, experiments, models, and prototypes while establishing technical standards, governance, reproducibility, and documentation. Coaches data scientists and analytics engineers and stewards critical data products end to end.

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 the architecture and evolution of a Snowflake-based operational data platform. Design secure, governed, scalable data warehouse solutions, real-time ingestion, API integrations, AI-enabled capabilities, and natural-language querying interfaces. Define data flows, schemas, roadmaps, architectural standards, and governance while collaborating with engineering, data, business, and executive stakeholders. Troubleshoot complex platform issues, guide technical direction, and promote modern data engineering practices across enterprise systems.

Leads architecture and evolution of Snowflake-based operational data platforms, including real-time ingestion, AI-enabled capabilities, API integrations, data modeling, governance, and secure enterprise data flows. Partners with engineering, data, and business stakeholders to define roadmaps, standards, and technical direction while troubleshooting complex systems and communicating architecture decisions to technical and executive audiences.

Monitor and analyze financial news, market data, company disclosures, ratings changes, deal terms, redemptions, and maturities. Maintain accurate investor relations details, reporting dates, datasets, and client-facing updates. Use HTML and proprietary tools to streamline publishing and data workflows. The role requires fast, accurate decision-making, strong communication, attention to detail, prioritization, and an interest in financial markets. Work follows rotating EU and US shifts.

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.

Lead national business development for JDP’s UK data centre sector. Build relationships with developers, operators, consultants, contractors, and supply chain partners; secure product specifications and project opportunities; convert new business; manage the project pipeline and sales forecasts; and represent the company at industry events. The role sells drainage, ducting, cable protection, water management, and infrastructure solutions.

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Lead the design and delivery of enterprise data architectures, strategies, governance frameworks, cloud platforms, and analytics solutions for defence, government, and regulated-sector clients. Responsibilities include stakeholder engagement, requirements analysis, architecture documentation, technical governance, project lifecycle leadership, business-case development, and support for proposals and customer presentations. The role also contributes to data capability development, emerging technology evaluation, and AI-enabled transformation.

Own operational delivery for complex research customer projects, including participant acquisition, onboarding, verification, activation, quality monitoring, and supply development. Build project plans, workflows, playbooks, and scalable processes while optimizing participant funnels and operational metrics. Partner with product, data, science, and customer success teams to improve time-to-data, fill rates, participant quality, and customer outcomes across Prolific’s Research platform.

Develop statistical and machine learning models using soccer tracking and event data to support player recruitment decisions. Build spatio-temporal models, metrics, analyses, and interpretation tools; validate models; communicate findings to professional club clients; and partner with engineering on cloud deployment and production reliability. The role also includes code review, model maintenance, and advancing analytical methods.

Leads electrical design for hyperscale and mission-critical data centers across Europe. Responsibilities include managing HV/MV/LV systems, substations, utilities, consultants, permitting, project delivery, construction support, commissioning, and integrated systems testing. The role provides client-side technical leadership, reviews designs and project documents, coordinates multidisciplinary teams, manages risks and milestones, and ensures compliance with standards and operational requirements.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

Leads Pure DC’s project management function across customer fit-outs, construction-to-operations handovers, lifecycle capital programmes, and internal projects. Owns customer relationships, budgets, contractor procurement, change management, commercial growth, risk, compliance, and delivery quality. Manages regional project teams and third-party partners across multiple geographies while establishing scalable governance, processes, and project controls.

As a Senior Data Science Engineer, you'll lead data science projects, develop algorithms, analyze datasets, and mentor junior team members to enhance trading operations and strategies.

Design, build, and maintain scalable data pipelines and platform services to support analytics, ML, and product teams. Implement infrastructure-as-code (Terraform) and Kubernetes-based deployments, develop data services/APIs, and ensure data quality, observability, security, and compliance. Partner with cross-functional teams, document systems, and continuously improve performance and reliability.

Manage international third-party data providers supporting identity verification, fraud prevention, KYC/eKYC, document verification, and compliance products. Responsibilities include vendor sourcing, due diligence, onboarding, contract and usage documentation, data quality and performance evaluations, integration coordination, issue resolution, renewals, cost tracking, and process improvement. Collaborate with Product, Data Science, Engineering, Legal, Compliance, Procurement, and external partners across global markets.

Leads complex enterprise customer engagements as a senior technical authority for data and AI architecture. Drives Databricks adoption, consumption strategy, executive relationships, competitive positioning, and large-scale architecture initiatives including migrations, real-time systems, lakehouse platforms, and AI/ML. Orchestrates cross-functional teams, mentors solutions architects, influences senior stakeholders, and contributes to technical thought leadership.

Own production NLP and applied AI systems that enrich scientific literature with entities, classifications, claims, and summaries. Design and evaluate classical NLP, embedding, retrieval, and LLM approaches; build scalable Python pipelines; manage cost, concurrency, reliability, and model quality. Collaborate with data engineers on Airflow and Dagster orchestration, contribute to agentic AI applications, and work with editors, product managers, and engineers to deliver research intelligence to users.

Build and operate NLP enrichment pipelines over scientific literature, extracting entities, classifications, claims, and summaries. Compare classical NLP, retrieval, embedding, LLM, and fine-tuned model approaches using evaluations, cost, quality, and operational metrics. Create golden datasets, define evaluation strategies, contribute to agentic AI applications, and collaborate with editors, product managers, engineers, SMEs, and vendors to deliver production modeling systems.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Build and evolve CluePoints’ enterprise data platform using Microsoft Fabric and Azure. Responsibilities include migrating Azure SQL and ADF workloads, integrating SaaS and web data, developing scalable ingestion and transformation pipelines, maintaining Kimball dimensional models, and establishing CI/CD, data quality, lineage, security, and monitoring. The role partners with analytics leadership and supports trusted Power BI reporting across multiple business functions.

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.