Global Cyber Data Lead - Hybrid Data Architect & Mentor

Marsh; Dublin; Hybrid; EUR 140,000 - 180,000; Full time

Job summary

Marsh in Dublin is seeking a Global Cyber Data Lead to lead our Cyber data engineering efforts in a hybrid role, requiring three days per week in the office. You will shape the data strategy, mentor engineers, and partner with cyber practice leadership to deliver scalable data solutions on platforms like Databricks.

You will drive DevOps/DataOps practices, collaborate with business teams, and stay ahead of technology trends to continuously improve data engineering across Marsh.

Qualifications

• 10+ years of data leadership experience.
• Strong proficiency in SQL and Python, with automation skills.
• Extensive experience with cloud data platforms (Databricks, Snowflake, Synapse) and cloud providers (AWS, Azure, GCP).
• Proven experience with Git, CI/CD pipelines, and DevOps/DataOps methodologies.
• Excellent English communication, written and verbal.
• Ability to identify and proactively solve complex data problems.

Responsibilities

• Lead design, development, and deployment of scalable data solutions.
• Mentor a team of data engineers and collaborate with cyber practice leadership.
• Partner with central platform teams to improve data operations efficiency and reliability.
• Drive DevOps/DataOps practices, including Git and CI/CD deployments.
• Collaborate with business teams to rapidly develop data solutions that fit evolving requirements.

Skills

SQL

Python

Databricks

Snowflake

Synapse

AWS

Azure

GCP

Git

CI/CD

DevOps/DataOps

Tools

Databricks

DBT

Job description

Marsh in Dublin is seeking a Global Cyber Data Lead to lead our Cyber data engineering efforts in a hybrid role, requiring three days per week in the office. You will shape the data strategy, mentor engineers, and partner with cyber practice leadership to deliver scalable data solutions on platforms like Databricks.

You will drive DevOps/DataOps practices, collaborate with business teams, and stay ahead of technology trends to continuously improve data engineering across Marsh.