Top Data Jobs in Belfast

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

Serve as the technical authority for enterprise customers in data security, owning the technical sales process. Deliver technical presentations, demos, and whiteboard sessions, advise on AI/ML-driven data protection, and drive outcomes through value-based selling with partners and GTM teams.

Leads North American indirect tax requirements and global tax data governance for an SAP S/4HANA transformation. Oversees U.S. and Canadian tax processes, tax determination, reporting, reconciliations, data standards, tax technology integrations, testing, deployment, audit readiness, and compliance. Partners across Tax, Finance, IT, Master Data, Analytics, Procurement, Supply Chain, and Shared Services to improve tax data quality and establish scalable global operating models.

Drive sales growth for Fluke’s data centre solutions across the UK, Ireland, and Nordics. Responsibilities include territory planning, prospecting, pipeline generation, forecasting, distributor and partner management, customer relationship development, product demonstrations, training, proposals, negotiations, CRM management, and industry events. The role requires technical understanding of data centre applications, consultative selling skills, and frequent engagement with end users, integrators, consultants, and channel partners.

Drive end-to-end B2B sales of Data and AI consulting services in the US market. Responsibilities include prospecting, pipeline generation, solution selling, account planning, business-case development, executive stakeholder engagement, partner collaboration, and closing enterprise and mid-market opportunities involving Databricks, Lakehouse modernization, data engineering, analytics, AI/ML, and GenAI.

Build and support reliable data pipelines, ETL processes, integrations, and data assets for financial crime platforms. Ensure data quality, integrity, availability, reconciliation, and production support for transaction monitoring, customer risk assessment, sanctions screening, regulatory reporting, analytics, and audit remediation. Collaborate with stakeholders, analysts, engineers, and vendors to investigate root causes and improve enterprise data capabilities.

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.

Design and deploy production data pipelines from ingestion through consumption using AWS cloud technologies. Build ETL pipelines, data warehouses, and data lakes; move and process large volumes of structured and unstructured data; integrate multiple sources; write scripts, extract data through APIs, and develop SQL queries. Collaborate with clients, stakeholders, product, design, and engineering teams using agile practices to deliver scalable digital solutions.

Lead design and delivery of production-grade AI/ML solutions for Kainos Workday products. Build predictive analytics, anomaly detection, generative AI features, and scalable MLOps pipelines. Integrate with Workday, mentor and line-manage a data science team, manage client engagements, and drive architectural and technical leadership across product initiatives.

Build and operate Python-based data ingestion, ETL, detection, and forensic artifact extraction pipelines for a mobile EDR platform. Productionize threat detection prototypes, optimize large-scale data storage and queries, deploy services on AWS, and establish monitoring, validation, fault tolerance, and data quality controls. Collaborate closely with security researchers to develop reliable tooling and scalable systems for identifying mobile spyware and other threats.

Lead design, engineering and delivery of cloud-native, Databricks/AWS-based data services. Drive migration to Databricks, build scalable Spark/Scala pipelines, optimize performance, mentor teams, manage technical delivery, and enable AI/GenAI integrations while ensuring governance, security and regulatory compliance.

Build and evolve a strategic Databricks-based Research data platform. Design scalable pipelines and governed data products using Python, SQL, Spark, Azure, Delta Lake, and ADLS. Implement ingestion, transformation, data quality, reconciliation, lineage, monitoring, audit controls, CI/CD, and deployment practices. Partner with global stakeholders and engineering teams to deliver analytics, BI, and AI-ready data capabilities while coordinating offshore delivery resources in India.

Curate and interpret drug discovery data from scientific papers, patents, and other disclosures. Responsibilities include interpreting chemical structures and biological data, building and maintaining databases, researching biopharmaceutical R&D, and surfacing accurate insights for scientific and industry audiences. The role requires strong data curation, patent literature, chemoinformatics, scientific communication, and attention to detail skills.

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.

Owns site maintenance planning, scheduling, work-order lifecycle management, CMMS administration, preventive maintenance programs, asset lifecycle planning, compliance controls, vendor performance, and KPI reporting. The role coordinates engineering teams, vendors, stakeholders, and global operations to maintain uptime, ensure audit readiness, implement change controls, and drive data-led maintenance improvements across data-center sites.

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.

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

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

Build large-scale data pipelines and infrastructure for frontier AI model training. Develop data-processing models such as classifiers, quality filters, and labeling systems; design deduplication, quality scoring, labeling, and augmentation strategies; and create reliable tooling for researchers to explore and train on massive datasets. The role also evaluates how data quality and composition affect model outcomes, with web crawler experience as a bonus.

Migrate SQL Server data products and analytical workloads to a modern cloud platform. Redesign legacy SQL, ETL processes, and business logic; build scalable pipelines and analytical models; validate data quality; collaborate with stakeholders; and improve platform reliability, performance, cost efficiency, and AI-assisted data engineering automation.