Top Data Engineer Jobs in Dublin

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Design, build, and maintain large-scale batch ETL pipelines and data lakehouse systems. Partner with Data Science, Product, and Engineering to define data ontology, develop tooling and automation, establish data operations standards and SLAs, mentor junior engineers, optimize large datasets, triage infrastructure issues, and prototype new metrics and analytics solutions to support AI-driven capabilities.

The Lead Data Analytics & AI Engineer will lead the technical strategy and engineering best practices for data modeling, ingestion, and advanced analytics, while mentoring engineers and collaborating across teams.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

As a Data Engineer at Yahoo, you'll implement AI/ML capabilities, build data pipelines, optimize workflows, and collaborate with teams to enhance user experiences.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Lead the design and technical delivery of HV substations for data centre clients. Oversee multi-disciplinary teams, ensure project timelines, maintain safety standards, and mentor junior engineers.

Build and enhance enterprise analytics and visualization solutions: develop interactive dashboards, data-driven apps, transform and prepare data with Python, implement frontend visualization components with TypeScript, integrate with Microsoft and Google enterprise ecosystems, and use AI tools to accelerate development while collaborating with stakeholders and owning deliverables end-to-end.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.