Hybrid Data Engineer — Real-Time Big Data Pipelines

UnitedHealth Group; Dublin; Hybrid; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

UnitedHealth Group's Optum unit in Ireland seeks a senior Data Engineer to design and implement automated data pipelines for production release of data engineering, ML and BI processes. You will transform data and collaborate with business and technology partners.

You'll bring extensive data engineering experience, advanced SQL, and hands-on work with cloud platforms (Azure, AWS, GCP) and big data tools like Hadoop, Spark, and Databricks.

Qualifications

• Proven extensive experience in Data Engineering.
• Advanced SQL proficiency.
• Experience with relational and non-relational databases.
• Experience implementing ETL, data warehousing, and data modeling in large-scale environments.
• Cloud experience across Azure, AWS, and GCP; Linux environments.

Responsibilities

• Design and automate data pipelines for production release of data engineering, ML and BI processes.
• Transform data to incorporate business logic with partners.
• Design, code, test, document, and maintain high-quality scalable Big Data solutions.
• Analyze raw data sources, data transformation, and structural requirements for new software.
• Migrate data from legacy systems to new solutions.
• Define security and backup strategy for data solutions.

Skills

Data Engineering

SQL proficiency

Python

Cloud platforms

Airflow

Big Data

Spark/Databricks

ETL/Data Warehousing

Agile/Scrum

dbt

Linux

Tools

Docker

Kubernetes

Spark

Databricks

Hadoop

Snowflake

Redshift

Synapse

Airflow

Kafka

Job description

UnitedHealth Group's Optum unit in Ireland seeks a senior Data Engineer to design and implement automated data pipelines for production release of data engineering, ML and BI processes. You will transform data and collaborate with business and technology partners.

You'll bring extensive data engineering experience, advanced SQL, and hands-on work with cloud platforms (Azure, AWS, GCP) and big data tools like Hadoop, Spark, and Databricks.