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Senior Data Engineer

G MASS
Dublin, County Dublin, Ireland Senior Posted

Summary

Written in English from the original posting

This is a Senior Data Engineer role with G Mass for a global financial services business, focused on building and maintaining enterprise data platforms. The role involves ETL/ELT pipelines, structured streaming, Spark, Databricks, Lakehouse architecture, governance, monitoring, and infrastructure support. Required experience includes 6+ years in data engineering, hands-on Databricks, Python, Spark, SQL, and AWS.

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

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