Top Data Engineer Jobs in Belfast

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

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.

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.

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.

Design, build, and scale cloud-native data warehouses and robust ETL/ELT pipelines (primarily BigQuery). Optimize performance, implement partitioning and cost controls, ensure data governance, observability, and regulatory reporting support, and collaborate with analytics and engineering stakeholders.

Own and operate Databricks production data pipelines for a predictive CRM platform: monitoring, incident response, cost and performance optimization, migrating legacy ETL, onboarding customers, enforcing Delta Lake architecture and multi-tenant isolation, and applying CI/CD, security, and observability best practices to ensure reliable, scalable data delivery.

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.

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

Build and maintain production data pipelines and features in Python; own project lifecycle from design to reliable production; set technical direction for the Insights platform; improve engineering standards (testing, observability, data quality); apply AI across products and pipelines; help establish semantic/AI-ready data layers.

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

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.

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.

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.

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.

Develop stored procedures or notebooks to build 230 additional data items into DCoE tables/views. Create an extensible, config-driven process to add fields with minimal re-engineering. Produce self-documenting, well-commented code and collaborate with the DCoE team on delivery; DCoE handles business analysis, design sign-offs, data modeling, and testing.

The Senior Data Engineer will enhance backend systems for a social media app by managing databases, optimizing recommendation algorithms, and ensuring accurate recommendations.

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

Design and deliver scalable Customer Data Platform solutions (Oracle Unity), build and operate data pipelines and Customer 360 models, integrate CDP with data lake/CRM/marketing systems, lead architecture and data modelling workshops, ensure data quality, governance, security, and support CDP operations, and partner with Oracle implementation teams.

Define and build quality frameworks for human data programs, partner with clients and engineering to design evaluation, recruitment and annotation strategies, implement automated checks and dashboards, investigate data integrity, and upskill teams to deliver high-quality human data at scale.

Lead data architecture and strategy across OLTP, OLAP, and AI systems. Drive AI-first foundations (LLM orchestration, RAG, real-time inference), ensure DataOps/CI-CD, mentor technical leads, run architectural reviews, partner with product and engineering leadership, and optimise platform security, observability and costs.

Design, build and maintain cloud-based data pipelines to deliver timely, traceable, audit-ready regulatory reporting for FATCA, CRS and PTR. Develop ETL/ELT workflows using Python, PySpark/Scala and SQL on AWS (Glue, S3, RDS/Aurora, DataSync). Integrate upstream via DIP, deploy via CloudBees/Jenkins, and ensure batch orchestration, reconciliation and regulatory compliance.

Implement, configure and debug web and mobile tracking and MarTech systems (Tealium, GA4, MMPs). Ensure data quality, privacy/compliance, QA and documentation while partnering with MarTech, CRM and Product teams.

Lead mechanical engineering projects for data centre design and delivery, collaborating with multi-disciplinary teams and contributing to strategic growth.

Design, build, and maintain scalable analytics models and automated reporting. Partner with Sales, Product, Marketing, and Finance to define KPIs, deliver ad hoc analysis, improve data quality and observability, and establish analytics engineering best practices to enable self-service analytics.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.