Top Data Engineer Jobs in Dublin

Design, build, test, and maintain scalable ELT/data pipelines and architectures using Python, Databricks, and AWS. Ensure data security and controls, update data models, and perform advanced SQL and statistical data analysis to support business analytics.

Leads the design and delivery of scalable data platforms and products for healthcare applications. Establishes standards for data modeling, quality, lineage, observability, testing, security, and operational readiness. Partners with product, AI, architecture, governance, and engineering teams to create technical roadmaps, reusable patterns, and multitenant architectures. Enables generative AI and conversational analytics solutions while mentoring engineers and evaluating architectural trade-offs.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates with product, architecture, governance, and business teams while supporting production readiness, platform modernization, and continuous improvement.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates with technical and business stakeholders, supports production systems, and contributes to platform modernization and continuous improvement.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates with product, architecture, governance, and business teams while supporting production systems, platform modernization, and continuous improvement.

Designs, develops, and supports secure, scalable cloud-native data products and platform capabilities. Builds batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates with product, architecture, governance, and business teams while supporting production readiness, platform modernization, and continuous improvement.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, Infrastructure as Code, and operational controls. Collaborates with product, architecture, governance, and business teams, while supporting production operations, platform modernization, and continuous improvement.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates across technical and business teams, supports production operations, and contributes to platform modernization. Preferred experience includes Kafka, data mesh, data contracts, AI/ML workloads, Terraform, and regulated industries.

Designs, develops, and supports secure, scalable cloud-native data products and platform capabilities. Builds batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates with product, architecture, governance, and business teams while supporting production systems, platform modernization, and continuous improvement.

Design, develop, and support cloud-native data products and platform capabilities. Build scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implement governance, security, observability, CI/CD, automation, and infrastructure as code. Collaborate across technical and business teams, support production systems, and contribute to platform modernization and continuous improvement.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates across product, architecture, governance, and business teams while supporting production operations and platform modernization.

Designs, develops, and supports secure, scalable cloud-native data products and platform capabilities. Builds batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, automation, and infrastructure as code. Collaborates across product, architecture, governance, and business teams while supporting production operations, modernization, data quality, and enterprise analytics solutions.

Designs, develops, and supports cloud-native data products and platform capabilities. Builds scalable batch and streaming pipelines using Databricks, Snowflake, Iceberg, Delta Lake, and cloud platforms. Implements governance, security, observability, CI/CD, infrastructure automation, and operational controls. Collaborates across product, architecture, governance, and business teams while supporting production readiness and continuous improvement. The role also contributes to platform modernization and data solutions for analytics, AI/ML, and data commercialization.

Design, build, test, and maintain scalable data engineering solutions, including automated releases, ETL processes, data models, real-time pipelines, monitoring, legacy migrations, and security strategies. Transform raw data using business logic, support machine learning and business intelligence workloads, and produce technical documentation. The role requires extensive experience with cloud platforms, SQL, databases, data warehousing, Spark, Databricks, Airflow, Kubernetes, Docker, Python, and related data technologies.

Leads architecture and development of backend services, APIs, integrations, and data systems that consolidate engineering, tooling, cost, and AI usage signals. Builds auditable reporting tools, owns reliability and monitoring, drives projects through rollout, collaborates with product and business stakeholders, and mentors engineers. The role requires backend, data modeling, SQL, full-stack prototyping, automated testing, production support, and hands-on agentic engineering practices.

Designs and maintains scalable Azure data pipelines, warehouses, models, ETL/ELT processes, dashboards, and analytics solutions. Uses Azure Data Factory, Azure Synapse, Power BI, Python, and SQL to transform data, optimize performance, resolve quality issues, and support business decisions. The role also involves Azure DevOps, CI/CD, data governance, GDPR compliance, Agile delivery, stakeholder collaboration, and leading data engineering initiatives.

Develop and maintain scalable data pipelines integrating databases, APIs, logs, streaming platforms, and external providers. Build transformation and processing jobs, implement governance and de-identification controls, monitor pipeline reliability, and establish automation and deployment best practices. Partner with analytics, product, infrastructure, and data science teams to advance cloud-based data and analytic platforms using Azure, Databricks, Snowflake, Spark, and SQL.

Build and maintain scalable production data pipelines, machine learning data pipelines, and data transformation frameworks for financial crime detection solutions. Collaborate with product, R&D, data, analytics, customers, and partners; optimize large-scale data architectures; support feature engineering and root cause analysis; and train customer teams. The role requires customer-facing collaboration, English and Spanish fluency, and domestic and international travel when needed.

Design, build, and maintain scalable ETL/ELT pipelines and data integrations to consolidate, transform, and prepare large datasets for analytics and ML. Enforce best practices, data governance, monitoring, and support while collaborating with business and analytics teams to improve data quality and enable insight-driven decisions.

Lead global strategy and operations for a cloud-native Service Delivery Platform, ensuring secure, scalable, and reliable service delivery across multiple cloud environments.

Build and maintain data pipelines and infrastructure for analytics, experimentation, and company metrics. Collaborate with machine learning engineers on training, quality assessment, and model release automation. Improve data delivery processes, automate manual workflows, and develop scalable data models. The role requires strong Apache Spark and Python expertise, SQL proficiency, Git experience, and familiarity with cloud data platforms and Kubernetes.

Build and maintain data pipelines, infrastructure, data models, and automation for analytics and machine learning workflows. Collaborate with ML engineers on model training, quality assessment, and releases. Improve internal data delivery processes and enable efficient access to large-scale organizational data.

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.

Lead hands-on design and delivery of scalable cloud-based data platforms and Lakehouse solutions, build high-volume batch and streaming pipelines, define standards for data modeling, quality, lineage, security, and observability, create reusable patterns, mentor engineers, and partner with product, AI, security, and governance stakeholders to enable analytics and AI use cases.

Build and operate AWS-based data platforms for fleet telematics products, including streaming and batch pipelines, ETL, data quality validation, observability, retention enforcement, and customer reporting. Own data engineering workstreams from architecture and design through deployment and production monitoring. Optimize database performance, cloud costs, and large-scale data systems while investigating production data issues and ensuring compliance.