Top Data Engineer Jobs in Dublin

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.

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.

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 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.

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.

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 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 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 product, architecture, governance, and business teams while supporting production systems, 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 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.

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.

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 evolve Toast’s cloud-native data platform, working hands-on with Spark, Iceberg, streaming infrastructure, lakehouse architecture, APIs, and feature-serving systems. Drive technical strategy and architectural decisions, influence engineering and product stakeholders, mentor engineers, and enable teams to build scalable data and AI/ML experiences. The role is hybrid in Dublin and supports major platform modernization initiatives.

Leads the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects cloud-based ETL/ELT, lakehouse, streaming, governance, and data quality solutions; modernizes legacy assets; optimizes processing; and establishes engineering standards, testing, deployment, and operational practices. Partners across risk, product, architecture, and engineering, influences technical direction, mentors engineers, supports compliance, and drives strategic roadmap execution.

Leads the design and implementation of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects Databricks, Spark, Delta Lake, and cloud-based solutions; establishes data quality, governance, lineage, security, monitoring, and operational standards; modernizes legacy systems; optimizes large-scale processing; influences technical strategy; mentors engineers; and partners with cross-functional stakeholders to deliver resilient, compliant data products.

Leads the design, development, and modernization of enterprise data platforms and pipelines supporting credit risk, analytics, regulatory reporting, and AI initiatives. Architects cloud-based ETL/ELT and streaming solutions using Databricks, Spark, Delta Lake, and related technologies. Establishes data quality, governance, lineage, security, monitoring, and operational standards while optimizing performance and cost. Partners with cross-functional stakeholders, influences architecture and roadmap decisions, mentors engineers, and drives delivery across complex initiatives.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI. Architects Databricks, Spark, Delta Lake, and cloud-based solutions; establishes governance, quality, lineage, observability, and security controls; optimizes large-scale processing; and guides technical strategy. Partners across risk, product, architecture, and engineering, mentors teams, influences stakeholders, supports compliance, and drives delivery across complex initiatives.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects cloud-based lakehouse solutions using Databricks, Spark, Delta Lake, and related technologies; establishes governance, quality, lineage, observability, security, and compliance controls; optimizes large-scale workloads; and drives technical standards, cross-functional delivery, mentoring, and strategic roadmap planning.

Lead the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architect cloud-based ETL and ELT solutions using Databricks, Spark, Delta Lake, and related technologies. Establish data quality, governance, lineage, observability, security, and compliance controls. Drive modernization, performance optimization, technical standards, cross-functional delivery, architectural decisions, mentoring, talent assessment, and strategic roadmap planning.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Builds scalable cloud-based ETL/ELT and streaming solutions using Databricks, Spark, Delta Lake, SQL, and Python. Establishes data quality, governance, lineage, security, monitoring, and operational excellence practices. Partners across risk, product, architecture, and engineering; influences technical direction, mentors engineers, supports compliance, and drives strategic roadmap execution.

Leads the design and delivery of enterprise data platforms and pipelines supporting credit risk, decisioning, analytics, regulatory reporting, and AI initiatives. Architects cloud-based lakehouse solutions using Databricks, Spark, Delta Lake, and modern ETL/ELT patterns. Establishes data quality, governance, lineage, observability, security, and compliance capabilities; modernizes legacy platforms; optimizes large-scale workloads; and drives engineering standards. Partners cross-functionally, influences architecture and roadmaps, mentors engineers, resolves complex dependencies, and supports technical hiring.