Senior Data Engineer - Lakehouse Pipelines & AI

G MASS Consulting; Dublin; On-site; EUR 110,000 - 150,000; Full time

Job summary

G MASS Consulting is seeking a Senior Data Engineer for a leading global Financial Services client in Dublin. This hands-on role sits at the center of an enterprise data platform, shaping architecture, driving pipeline development, and contributing to AI initiatives across a high-volume data environment.

You will design scalable Lakehouse solutions, develop ETL/ELT and streaming workflows, tune Spark jobs, and implement governance with Delta Lake, Unity Catalog, and IAM.

Qualifications

• 6+ years in data engineering with hands-on Databricks experience.
• Strong Python and Spark programming skills.
• Solid AWS experience including S3, Glue, and Lambda.
• Deep understanding of data modelling, SQL and ETL/ELT design patterns.
• Experience with Delta Lake and Lakehouse architecture.
• Demonstrated use of AI tools within a professional development workflow.
• Strong communication across technical and non-technical teams.

Responsibilities

• Design and develop scalable data solutions on a Lakehouse platform for enterprise-wide data processing and analytics.
• Build, optimise, and maintain ETL/ELT pipelines and streaming workflows for batch and real-time data ingestion.
• Configure and tune clusters and Spark jobs for consistent performance at scale.
• Utilise Delta Live Tables and Unity Catalog to manage data ingestion, transformation, and access governance.
• Apply IAM best practices and maintain compliance with data security standards.
• Support infrastructure provisioning and resource management using Terraform.
• Implement monitoring frameworks for pipeline performance and data quality.
• Contribute to code reviews, documentation, and knowledge sharing.
• Collaborate with data scientists, analysts, and business stakeholders in an Agile environment.
• Explore emerging technologies and AI tooling to boost productivity and platform capability.

Skills

Databricks

Python

Spark

AWS

SQL

Data modelling

ETL/ELT design

Tools

Delta Lake

Delta Live Tables

Unity Catalog

Terraform

Git

S3

AWS Glue

AWS Lambda

Job description

We are working with a leading global Financial Services business to hire a Senior Data Engineer into their growing data engineering practice. This is a hands-on technical role sitting at the centre of a major enterprise data platform build, with scope to influence architecture, drive pipeline development, and contribute to AI initiatives across a complex, high-volume financial data environment.

Responsibilities

• Design and develop scalable data solutions on a Lakehouse architecture platform, supporting enterprise-wide data processing and analytics
• Build, optimise, and maintain ETL/ELT pipelines and structured streaming workflows for both batch and real-time data ingestion
• Configure and tune clusters and Spark jobs to deliver consistent performance at scale
• Utilise Delta Live Tables and Unity Catalog to manage data ingestion, transformation, and access governance
• Apply IAM best practices and maintain compliance with data security standards across the platform
• Support infrastructure provisioning and resource management using Terraform
• Implement monitoring frameworks covering pipeline performance, data quality, and operational health
• Contribute to code reviews, technical documentation, and team knowledge-sharing
• Work within an Agile delivery model, collaborating closely with data scientists, analysts, and business stakeholders
• Explore emerging technologies and AI tooling to enhance development productivity and platform capability

Requirements

• 6+ years in data engineering, with at least 2 years hands-on experience with Databricks
• Strong Python and Spark programming skills
• Solid AWS experience across core services including S3, Glue, and Lambda
• Deep understanding of data modelling, SQL, and ETL/ELT design patterns
• Experience with Delta Lake, Lakehouse architecture, and Git-based version control
• Demonstrable use of AI tools within a professional development workflow
• Strong communication skills and the ability to work effectively across technical and non-technical teams

Desirable

• Financial services or fund administration background
• Exposure to AI/ML implementation patterns and real-time data processing frameworks
• Multi-cloud experience beyond AWS
• API development or data governance framework experience
• Experience mentoring junior engineers

Benefits

• Salary: to be discussed, depending on experience
• Length: Permanent contract