Data Engineer - Hybrid Real-Time Data Pipelines

Optum; Letterkenny; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

Optum is seeking a data engineer to advance our data analytics and AI-driven healthcare initiatives. You will design and implement automated data pipelines, transform complex datasets, and build robust Big Data solutions across cloud platforms.

You will collaborate with partners to apply business logic and ensure scalable, secure data flows. Strong SQL, Python and Spark/Databricks experience are essential, as is familiarity with Airflow, Kubernetes and Docker in a Scrum/Agile setting.

Qualifications

• Proven extensive experience in Data Engineering.
• Proven experience with data processing technologies and SQL databases.
• Advanced SQL proficiency.
• Experience with relational and non-relational databases.
• ETL design and data warehousing/data modeling in large-scale environments.
• Public cloud experience (Azure/AWS/GCP); Linux environments.

Responsibilities

• Design, build and implement automation for data pipelines and data engineering processes.
• Transform data and apply business logic in collaboration with partners.
• Develop scalable Big Data solutions and maintain documentation.
• Migrate data from legacy systems to modern platforms.
• Create data models, flowcharts and ensure security/backup strategies.
• Prototype real-time data pipelines and monitoring models.

Skills

Data engineering

SQL proficiency

Python

Java/Scala

Spark/Databricks

Airflow

Kubernetes/Docker

Cloud platforms (Azure/AWS/GCP)

Data modeling

Agile/Scrum

Kafka

dbt

Tools

Hadoop

Snowflake

Vertica

Redshift

Synapse

Apache Airflow

Kubernetes

Docker

Databricks

Job description

Optum is seeking a data engineer to advance our data analytics and AI-driven healthcare initiatives. You will design and implement automated data pipelines, transform complex datasets, and build robust Big Data solutions across cloud platforms.

You will collaborate with partners to apply business logic and ensure scalable, secure data flows. Strong SQL, Python and Spark/Databricks experience are essential, as is familiarity with Airflow, Kubernetes and Docker in a Scrum/Agile setting.