Top Data Jobs in Belfast

Design, experiment, and validate NLP/LLM and generative AI solutions for patent intelligence. Develop agentic workflows, retrieval strategies (hybrid semantic+lexical), evaluation metrics, and large-scale text processing methods. Partner with product and engineering to translate validated models into scalable, customer-facing features and deliver measurable business impact.

The Forward-Deployed Data Analyst will engage with African Ministries of Health, build data management solutions, develop dashboards, and support public health decision-making.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Lead development of ClickHouse's Python connector and SDKs, build integrations with orchestration and transformation tools, drive AI/LLM integration strategy for production data workflows, engage with open-source community, and collaborate across product and platform teams to deliver enterprise-grade data integrations.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.

Lead and mentor a squad building and operating CDC and streaming data pipelines from DB2/VSAM/Oracle to Kafka and HDFS. Ensure platform reliability, security, compliance, incident response, scalable designs, service SLAs, tooling standards, and stakeholder/vendor management while driving continuous improvement.

The Data Product Analyst designs and manages data products for insurance domains, ensuring they meet analytical and compliance standards while collaborating with cross-functional teams.

As a Senior Data Engineer at YLD, you'll design and build scalable, resilient data-driven solutions, collaborating with cross-functional teams to innovate and enhance productivity through AI tools.

Lead the development of backend services for government clients, focusing on high availability and scalability, while collaborating in agile teams and maintaining deployment pipelines.

The Lead Data Architect will shape data strategy, design secure data architectures on AWS, mentor teams, and ensure compliance with regulations.

Lead Kraken's Data Platform team focused on real-time infrastructure for data systems, managing team dynamics, architecture design, and promoting AI automation.

As a Lead Data Scientist, you will set technical direction, ensure project delivery, manage client relationships, and mentor data scientists.

The Software Engineer will provide technical support to customers, collaborate with engineering teams, and drive customer success initiatives while leveraging Python and SQL expertise.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.

Build, optimise and stabilise AWS-based data pipelines (S3, Glue, Redshift, Lake Formation). Resolve technical debt, support the Architect on target-state design, collaborate with client engineering teams to transfer knowledge, and deliver production-ready platforms in regulated, high-volume gaming environments.

Perform data profiling and validation for a large-scale public-sector data migration. Define and execute data quality rules, run SQL (MySQL) and stored procedures, test BI dashboards, document findings, and liaise with engineers and stakeholders to ensure accuracy, completeness, consistency, timeliness, validity and uniqueness of migrated data.

Perform data collection, analysis, and interpretation to identify trends. Build and maintain dashboards and reports, ensure data accuracy through quality checks, collaborate with teams to deliver actionable insights, and support development of analysis methodologies.

As a Senior Data Engineer, you will manage complex data projects, lead small teams, and work with clients on data engineering solutions. Responsibilities include ETL development, data pipeline orchestration, and customer relationship management.

Lead project teams in delivering bespoke algorithms, mentor other data scientists, and shape client relationships in the defence and national security sector.

The Curriculum Manager will oversee the content development lifecycle, recruit instructors, design curriculum, assess course performance, and improve data science and engineering content.

Short-term consultant to maintain WaterAid's research and data monitoring functions: manage the KRSP, integrate and format databases into the Statistics Bank/Power BI, update JMP/GLAAS WASH datasets, produce monthly KRSP usage reports, convene research clinics, and support research design, procurement and quality assurance over a four-month assignment.

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.

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.