Top Data Engineer Jobs in Belfast

Lead the design and development of data services, manage data reliability, create data models, and ensure data products support ML workflows.

Consult as part of a team building high-performance, cloud-native data platforms for financial markets. Design and implement scalable data pipelines, data models and analytical workloads using Python, SQL and ClickHouse. Deploy and optimise ClickHouse in client environments, work with distributed architectures, container orchestration and automation tools, and collaborate directly with client engineering teams.

The Data Engineer will design and deploy production data pipelines, work with AWS technologies, and integrate data from various sources while collaborating with teams and stakeholders.

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.

Design and build production data pipelines on AWS from ingestion to consumption. Process large structured and unstructured datasets, integrate multiple sources, write ETL scripts and SQL, and collaborate with cross-functional teams using agile practices.

Design, build, and support production ETL/ELT data pipelines across a cloud data stack. Partner with engineers and analysts to deliver reliable, well‑modeled data, ensure data quality and failure handling, tune SQL and warehouse objects, and handle semi‑structured formats like JSON and Parquet.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

As a Data Engineer, you will design, build, and maintain data pipelines and infrastructure to support data-driven decision-making in a collaborative environment.

The Data Engineer will design and support data warehouses, create analytics dashboards, perform data quality analysis, and identify process improvements. Responsibilities include collaborating with stakeholders to develop insights and ensure data governance.

The Data Engineer will build and manage scalable data pipelines and databases, collaborate on architecture, and drive data systems towards real-time capabilities in a fast-paced, innovative environment.

Support ledger migration and data lake cleanup by extracting, transforming, reconciling and validating large datasets. Develop and validate SQL queries, batch jobs and processing logic, perform regression testing, document mappings and validation rules, and collaborate with engineering, product and business teams to ensure production readiness and post-migration validation.

Client-facing Principal Data Engineer leading design and delivery of enterprise Databricks-based data platforms. Provide architecture leadership, mentor engineering teams, drive platform optimisation, define standards, support technical governance, and deliver across multiple consultancy engagements.

Design, build, and maintain high-volume distributed data processing jobs and pipelines (Redshift, Athena, Iceberg, Spark, Airflow). Collaborate with data scientists and analysts to productionize models, optimize performance, troubleshoot systems, and mentor junior engineers. Support lakehouse/data warehouse management and ensure data accuracy and efficiency.

Design, build, and maintain scalable batch and streaming data pipelines, internal tools, and APIs to support analytics, product features, and ML. Collaborate with product and engineering to improve data infrastructure, ensure reliability, testing, and observability in a cloud-native environment.

The Data Engineer will build and scale data pipelines, ensure data quality, implement dbt best practices, and empower cross-functional teams with self-service data access.

Lead client-facing data platform architecture and strategy. Design scalable Databricks/Azure or AWS-based solutions, oversee multi-team delivery, incident response, governance, and data security. Mentor engineers, drive roadmap and budget decisions, and ensure resilient, high-quality data pipelines aligned to business goals.

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

Entry-level data engineer to follow a structured 12-month development programme. Build internal reporting, reusable engineering frameworks, documentation, and tooling while learning SQL, Python, Databricks and cloud data services. Support senior engineers, join code reviews, shadow customer workshops, and progressively contribute to client projects.

Design, build and maintain cloud-native ETL/ELT pipelines and data lake solutions using dbt, Snowflake/Databricks and AWS services. Optimize SQL and data models for performance and cost, create dashboards, follow CI/CD and software engineering best practices, and collaborate with architects, engineers and clients to deliver production-ready enterprise data solutions.

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 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.

The Software Engineer will enhance data collection and ingestion pipelines for AI model training, collaborating on dataset roadmaps and managing cloud infrastructure.

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.

The role involves developing data pipelines, managing metadata and data quality in Azure, ensuring compliance with data governance standards, and collaborating with data teams.