Top Data Engineer Jobs in Belfast

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.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

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

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.

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.

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.

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.

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.

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.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

The Senior Site Reliability Engineer will design and maintain a reliable data platform, develop data pipelines, automate processes, and ensure system observability while collaborating across teams.

Design, build, and support large-scale data systems and pipelines, ensuring reliability and scalability while collaborating with cross-functional teams to meet data requirements.

Lead end-to-end development and productionisation of time-series forecasting ML solutions: design, train, deploy models, build cloud-native data pipelines, collaborate with stakeholders, and monitor model performance to optimise clinic scheduling and staffing.

This role involves designing and optimizing a blockchain data platform, focusing on ETL pipeline development, data quality, and system scalability. The engineer will collaborate with cross-functional teams to enhance data access and enable product engineering efforts.

The Senior Data Engineer will design and maintain scalable data pipelines, ensure data quality, and develop backend services to support WalletConnect's payments infrastructure and analytics.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

Design and implement core YTsaurus functionality in C++, build and evolve platform-level capabilities, improve APIs and UX for internal users, own production quality including incident response/on-call, and collaborate with stakeholders to prioritize and deliver scalable data platform features.

As a Senior Data Engineer, you will design and develop large-scale data processing software, manage technical components, and mentor team members, while ensuring code quality and operational readiness.

As a Senior Data Engineer, you'll design and develop data processing solutions, collaborate with architects, mentor team members, and ensure operational readiness in agile teams.

Build and maintain scalable data pipelines and platform components to serve analytics, ML, and product teams. Design data services/APIs, ensure data quality, observability, security and compliance, and evolve cloud-native infrastructure using IaC and Kubernetes. Partner with cross-functional teams, produce documentation, and ship reliable, tested data solutions.

Build, test, and document secure batch and real-time data pipelines for a government client; design logical and physical databases; extend platform capabilities; ensure data models align with architecture; perform data analysis and root-cause investigations to improve processing and availability for downstream consumers.

Design, build, test and document secure batch and real-time data pipelines, perform logical/physical database design and data modelling, expand platform capabilities, analyse and resolve data processing issues, and ensure alignment with data architecture for downstream consumers.

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.