Top Data Engineer Jobs in Dublin

As a Senior Data Engineer, you'll develop and maintain ETL data pipelines, integrate data from multiple sources, ensure data quality, and support analytics and ML tasks. You'll also collaborate on architecture and best practices.

The role involves developing capabilities for data parsing and enrichment in a cloud environment, leading cross-team initiatives, and ensuring high availability in distributed systems.

Lead design, build, and operate scalable data pipelines and products to support foundation models and AI workloads. Own ingestion, transformation, feature engineering enablement, data quality, governance, and production readiness while mentoring engineers and ensuring enterprise standards.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Ensure data quality, lineage, governance, and performance across batch and streaming workloads; enable feature engineering and feature stores; mentor engineers and drive delivery with platform and product teams.

Lead design, build, and operate scalable data pipelines and data products for foundation-model training, inference, and evaluation. Ensure data quality, lineage, governance, and performance; enable feature engineering and training datasets; collaborate with AI, platform, and product teams; mentor engineers and oversee delivery.

Lead design, build, and operate scalable data pipelines and products for AI foundation models. Own ingestion, batch and streaming transforms, feature engineering and training datasets, ensure data quality, lineage, governance, performance tuning, and secure access. Collaborate with AI, platform, and product teams, lead technical reviews, mentor engineers, and contribute to program planning and delivery.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Ensure data quality, governance, lineage, and secure access. Partner with AI, platform, and product teams, drive best practices, conduct reviews, mentor engineers, and manage delivery risks for AI data needs.

Lead design, build, and operate scalable data pipelines and products to support foundation model training, inference, and evaluation. Own ingestion, transformation, streaming and batch patterns, feature engineering support, data quality, lineage, governance, and performance optimization. Collaborate with AI, platform, and product teams, lead technical reviews, mentor engineers, and contribute to program planning and delivery oversight.

Lead design, build, and operate scalable, governed data pipelines and products for AI model training, inference, and evaluation. Partner with AI engineers, ensure data quality, lineage, governance, and performance; mentor engineers and drive delivery.

Lead design, build, and operate scalable data pipelines and data products to support foundation model training, inference, and evaluation. Partner with AI and platform teams to enable feature engineering, ensure data quality, governance, lineage, and secure access. Drive best practices for modeling, partitioning, performance, monitoring, and CI/CD. Provide technical leadership, code/design reviews, mentoring, and program-level planning to ensure production-ready, reliable data for AI workloads.

Lead design, build, and operate scalable data pipelines and products for foundation model training, inference, and evaluation. Own ingestion, transformation, batch/stream processing, feature engineering, data quality, lineage, governance, and performance tuning. Collaborate with AI, platform, and product teams to ensure production readiness, security, and observability. Provide technical leadership, code/design reviews, mentoring, and delivery planning across the program.

Lead design, build, and operate scalable data pipelines and products for AI model training, inference, and experimentation. Ensure data quality, lineage, governance, and performance; enable feature engineering and feature stores; collaborate with AI, platform, and product teams; mentor engineers and oversee delivery.

Lead design, build, and operate scalable, governed data pipelines and products for foundation models and AI workloads. Partner with AI and platform teams to enable feature engineering, training/inference datasets, data quality, lineage, and secure access. Provide technical leadership, code/design reviews, mentoring, and delivery planning across cloud-native distributed data environments.

As a Principal Data Engineer, you will lead the architecture and development of scalable data solutions, mentor engineers, and influence data practices across the business using Python, SQL, and modern data tools.

Join an Agile data engineering team to migrate analytics from Oracle to Microsoft Fabric. Design and build data pipelines, metadata-driven ingestion and orchestration frameworks, perform integration testing and data mirroring, contribute to analytics data modelling, and support Microsoft Purview implementation for scanning, cataloguing, and governance.

The Data Engineer will analyze data to drive business insights, create dashboards, and collaborate with teams to optimize product performance using SQL and visualization tools.

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.

The Data Engineer will support backend operations by building and maintaining ETL/ELT pipelines, monitoring data integrity, and creating datasets for reporting across teams.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The Data Engineer will translate business objectives into actionable analytics, develop Big Data applications, automate quality checks, and collaborate on data privacy compliance.

Hands-on senior data engineer to design and build scalable Lakehouse data solutions, develop ETL/ELT and streaming pipelines, tune Spark workloads, manage Delta Lake ingestion and governance, implement infrastructure with Terraform, enforce IAM and data security, monitor pipeline health, collaborate in Agile with data scientists and stakeholders, and explore AI tooling to enhance the platform.

The role involves developing and maintaining data models, managing data pipelines, ensuring data quality, and collaborating with business teams to create robust data solutions.

Design, build, and operate large-scale cloud-native data pipelines and lakehouse/warehouse solutions using Databricks, Snowflake, Spark/PySpark and Delta Lake. Implement MLOps practices, ensure data quality and governance, collaborate with architects and product owners, and support BI/ETL tooling and CI/CD for production deployments.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.