# Data Engineering Team Lead - Databricks

**Company:** [G MASS](http://jobs.workable.com/companies/91YsMDGMxxHFRTgqyt1Uj9.md)
**Location:** Dublin, Ireland
**Workplace:** hybrid
**Employment type:** Full-time

[Apply for this job](http://jobs.workable.com/view/e8901a1f-6422-43ef-9a9c-12c14288f013)

## Description

We are working with a leading global Financial Services business to hire an experienced Data Engineering Team Lead to head up a team of engineers working across a large-scale enterprise data platform. This is a senior hands-on leadership role requiring both deep technical expertise and the ability to drive delivery, mentor talent, and set standards across a distributed engineering function.

**Responsibilities:**

-   Lead, mentor, and develop a team of data engineers across multiple locations, driving code reviews, design reviews, and a culture of knowledge-sharing
-   Own and drive Agile/Scrum delivery processes, ensuring the team operates effectively against roadmap priorities
-   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 uphold compliance with data security and governance standards
-   Support infrastructure provisioning and resource management using Terraform
-   Implement monitoring frameworks covering pipeline performance, data quality, and operational health
-   Contribute to technical documentation and promote continuous improvement across the engineering practice

## Requirements

-   8+ years in data engineering, with at least 3 years hands-on experience with Databricks
-   Proven experience leading and managing a team of data engineers
-   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 leadership, communication, and stakeholder management skills

**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
-   Track record of developing junior and mid-level engineers in a fast-paced environment

## Benefits

Salary: to be discussed, depending on experience

Length: Permanent contract