Top Data Engineer Jobs in Dublin

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

Build and architect an in-house data warehouse and pipelines, enforce data governance and security, enable advanced analytics and reporting, and reduce reliance on external data providers to support credit and markets investment analytics.

Design, build, and maintain ELT pipelines and dbt SQL models for analytics; optimize performance, scalability, and costs; apply AI-enabled tools to improve engineering workflows; collaborate to translate requirements into production-grade data assets.

Design, build, and maintain ETL/ELT data pipelines and processing jobs (PySpark/SQL) on cloud platforms (Azure, Databricks, Snowflake). Ensure data quality, governance, monitoring, and automation; partner with analytics and infrastructure teams to productionalize analytic pipelines and support platform architecture.

Design, develop, and maintain ELT/ETL Snowflake data warehouse solutions; implement data standards, CI/CD, monitoring, and production support; collaborate with product, business, and vendors; mentor junior developers and improve data engineering practices.

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.

Design, build, and operate scalable Databricks data pipelines and Lakehouse data models using SQL, Python, and PySpark. Implement ELT/ETL and streaming patterns, data quality checks, Unity Catalog governance, performance optimization, monitoring, documentation, and operational support.

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.

Build and maintain BigQuery data models and ETL pipelines using Dataform and Python; implement data quality and observability; schedule workflows with Cloud Composer/Airflow; support Looker reporting and ML feature pipelines; collaborate with Data Science and Product to productionize analytics.

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.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

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.

Lead technical direction for ResMed's data ecosystem: design Snowflake/dbt models, build resilient data pipelines (Python, Spark, APIs), establish governance and CI/CD (GitHub Actions), mentor engineers, and enable classical and generative AI/ML feature pipelines and workflows.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

As a Data Engineer, you will develop and manage data pipelines, ensuring reliable data ingestion and delivery while optimizing for simplicity and performance.

Build and maintain AI-enabled business applications and integrations, help design and own application data models and databases, support AI architecture, data governance, ingestion and deployment, and collaborate across teams to translate business needs into scalable technical solutions.

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.

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.

The Data Scientist will develop and deploy AI/LLM models for security solutions, collaborate across teams, and ensure robust deployments.

Design, build, and maintain large-scale data pipelines, lakehouse and analytics systems. Develop frameworks, SLAs, complex queries, and collaborate with engineers and data scientists to deliver data-driven solutions and prototypes.

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.

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.