Data Engineer Jobs

Data engineering — the discipline of building and maintaining the pipelines that move data from source systems to analytical platforms — has 52 active roles in Ireland, with Dublin (27) leading and Cork (7) providing a secondary hub.

The employer base is diversified. Fisher Investments leads with 4 positions for its European wealth management data infrastructure. Canonical recruits 3 data engineers remotely for Ubuntu telemetry and product data pipelines. SoSafe has 3 positions for its cybersecurity awareness platform's data stack. UnitedHealth Group recruits 3 data engineers building healthcare analytics pipelines at scale. Analog Devices in Limerick and EY in Dublin each contribute 2 positions.

F5 recruits data engineers for network performance analytics from its Dublin engineering centre. Intercom hires data engineers to power the analytics behind its AI customer service products. Percona adds a database-engineering flavour — the company specialises in open source database software (MySQL, PostgreSQL, MongoDB), making its data engineering roles distinctively infrastructure-focused.

The Cork cluster is notable: with 7 positions it represents the strongest regional concentration outside Dublin for this discipline, driven by a mix of pharma-tech crossover companies and growing tech operations. The evolution of the modern data stack has fundamentally changed what data engineers do — the shift from batch ETL jobs running overnight to real-time streaming architectures using Kafka and Flink means that data engineers are increasingly building systems that must operate with the same uptime and reliability expectations as production applications. This blurring of the boundary between data engineering and software engineering is reflected in job descriptions that frequently list CI/CD, containerisation, and infrastructure as code alongside traditional data skills.

What distinguishes data engineering from data science or data analysis? Data engineers build the systems — the ETL/ELT pipelines, data warehouses, streaming platforms, and data lakes — that data scientists and analysts consume. The core skills include SQL and Python at the foundation, with Spark, Airflow, dbt, Kafka, and Snowflake/BigQuery/Redshift forming the modern stack. Knowledge of data modelling, data quality frameworks, and orchestration is essential. Cloud-native data engineering using AWS Glue, Azure Data Factory, or GCP Dataflow is increasingly the norm. The career path runs from Data Engineer through Senior Data Engineer to Staff Data Engineer, Principal Data Engineer, and Head of Data Engineering — with strong compensation reflecting the critical infrastructure nature of the role.