Top Data Jobs in Belfast

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.

Embedded within the commercial team, the Senior Data Analyst will own core sales and revenue metrics, improve pipeline and forecast accuracy, investigate CRM data quality, size commercial opportunities, and analyze partner, retention, and renewal performance. The role translates ambiguous business questions into actionable recommendations, defines trusted metric frameworks, communicates insights to senior stakeholders, and increases self-service analytics adoption across non-technical commercial teams.

Drive enterprise sales for Semrush’s big data and emerging solutions. Serve as a subject-matter expert, partner with Account Executives on team selling, conduct product demonstrations, translate complex capabilities into customer value, identify expansion opportunities, provide product feedback, support launches and events, and maintain deep product knowledge. The role requires enterprise sales experience, solutions selling expertise, familiarity with DaaS, SaaS, or big data analysis, and strong storytelling skills.

Leads the strategic development, governance, and evolution of TM Forum’s Open Digital Architecture, with a focus on AI and data. Collaborates with telecom and technology stakeholders to create architecture artifacts, align standards, guide implementations, manage roadmaps, and drive adoption. Represents TM Forum through industry thought leadership and explains complex technical concepts to diverse audiences. Requires extensive enterprise or solution architecture experience, cloud-native expertise, API design knowledge, and strong stakeholder communication skills.

Design, build and deploy production data pipelines and big-data architectures on AWS. Ingest, process and curate large structured and unstructured datasets, integrate multiple sources, write ETL scripts and SQL, and collaborate with cross-functional teams to deliver data warehouse and data lake solutions.

Lead technical design and delivery of advanced AI solutions (ML, generative and agentic AI), drive adoption of modern AI engineering and cloud-native architectures, ensure responsible AI practices, mentor and manage a small team, and liaise with clients to translate business needs into production-grade, secure AI systems.

Lead customer underwriting proof-of-concept projects using SQL, Python, and AWS to transform, validate, and deliver insurance risk data. Match address data to reference identifiers, investigate data-quality issues, document outputs, support underwriting data platforms, and automate manual workflows. Collaborate with technical and non-technical stakeholders, communicate project updates, and improve scalable data processes, quality, and customer experience.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, generative AI, retrieval, and hybrid search. Define multi-step reasoning workflows, analyze large-scale intellectual property datasets, establish model evaluation and benchmarking practices, and translate experiments into product recommendations. Collaborate with product teams, intellectual property experts, and engineers to deliver scalable, customer-facing solutions.

Lead and grow a Data Science team to deliver end-to-end, scalable ML/AI solutions for online personalisation. Partner with product, engineering and commercial teams to embed models, set standards for agile delivery, testing and model monitoring, and drive innovation to improve customer experiences and business value.

Design, build and maintain scalable, automated cloud data solutions and pipelines. Provide technical leadership to a small engineering squad, own complex backlog tasks, develop data frameworks and standards, and ensure code quality via reviews and pair programming using Databricks, Python, SQL and Spark.

Design and maintain reliable data solutions, lead a squad of engineers, develop scalable data pipelines, and ensure adherence to data standards.

Leads complex machine learning delivery and Defence-sector strategy, translating client challenges into technical roadmaps, scoping projects, managing client relationships, and supporting technical sales. Writes production-grade Python, serves as a machine learning authority, develops Generative AI and agentic AI solutions using LLMs, and mentors and manages data scientists.

Lead and develop a Data Science team to deliver scalable ML/AI solutions for an online Personalisation programme, ensuring impactful customer experiences.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Lead measurement, reporting, and optimization of global marketing performance. Build dashboards and reporting frameworks across GA4, Salesforce, Pardot, paid media, and social. Analyze campaign, funnel, pipeline, and ROI performance, establish KPI definitions and governance, and provide actionable insights to marketing, sales, and executive stakeholders.

Senior Data Engineer responsible for delivering and maintaining data engineering solutions, including Hadoop, Spark, Airflow, data streaming, and CDC workflows. The role involves diagnosing complex technical issues, applying secure development and quality practices, supporting CI/CD and containerization, evaluating technologies and vendors, and mentoring engineers. Collaboration with technology teams and banking stakeholders is required, with strong attention to service delivery, risk, compliance, Agile delivery, and DevOps practices.

The Finance Data Manager will analyze complex financial and operational datasets, translate business requirements into scalable data assets, and deliver management reporting and commercial insights. Responsibilities include collaborating on data pipelines, automating financial reporting with code and AI, building reporting solutions, improving processes, and partnering with stakeholders across the business.

As a Data Architect, you'll lead traditional data architecture practices, provide technical guidance, manage a team, and engage with clients.

Lead design and implement data strategy and architectures for Funds (IBOR/ABOR, fund accounting, ETFs). Drive data modeling, governance, lineage, integration, and enable reporting while collaborating with engineering and stakeholders.

Analyze and integrate multiple data sources, build conformed data models, and create accessible Power BI dashboards and reports. Apply statistical techniques including regression, correlation, and significance testing to generate actionable insights. Clean and transform data using SQL, Python, Power Query, and M, while communicating findings to technical and non-technical stakeholders and recommending emerging visualization technologies.

Annotate and segment videos, write objective captions, label visually verifiable actions, and review AI-generated captions for accuracy and consistency. Specialists must follow detailed guidelines, maintain at least 95% benchmark accuracy, and complete a paid certification process involving training, platform practice, and five certification tasks before accessing ongoing production work.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.