TechJobs.ie Job Insights
At a glance
- Employment type
- Full-time
- Location
- Galway, Ireland
- Workplace
- On-site
- Category
- Data engineering
Technologies & skills
What you'll be doing
Senior Data Engineer role in Galway, Ireland, focused on processing and generating analytics from structured and unstructured datasets. The position emphasizes enterprise development, scalable applications, and rapid prototyping, with exposure to AI/ML workflows and cloud technologies, primarily using Python, Java, or C#.
Key requirements
Must-have
- Bachelor’s or Master’s Degree in a technology related field
- Strong experience in RDBMS
- Strong experience in AWS
- Experience with object oriented programming principles and data structures
- Experience using CI/CD tools
- 6+ years of enterprise development
- Ability to balance multiple tasks concurrently
- Experience in planning, designing, leading, and executing technical solutions
Nice-to-have
- Experience with migrating applications to AWS
- Experience with Pandas or NumPy
- Experience with Snowflake
- Experience with PL/SQL
- Exposure to prompt engineering for LLMs such as OpenAI’s GPT-4, Google Gemini, Anthropic Claude
Experience: 6+ years of enterprise development
Role signals
- Technical focus
- data engineering, analytics, scalable applications, rapid prototyping
- Leadership
- Mentoring
- Architecture / system design
- Indicated in the listing
- Hands-on vs management
- Hands-on
Similar jobs
Full job description
We are currently seeking a Senior Data Engineer to work on Asset Management’s Advanced Strategies & Research Technology (AS&R) Team.
The AS&R Team within the Asset Management organization is an embedded team passionate about unlocking the potential of new technologies, techniques and datasets, to assist Investment Professionals in generating alpha for investment products and customers.
The role is ideal for someone with an enterprise development background, with a strong technology, coding and data skills, looking to operate in a less constrained environment, as part of an accelerated development team.
The role is ideal for a skilled technical leader with strong design, teamwork and influencing skills.
Ideally the candidate is a full stack, but this role will be primarily focused on processing and generating Analytics from structured and unstructured datasets with the ability of parallel processing potentially in the cloud.
The successful candidate will have the opportunity to get exposure to prompt engineering for Large Language Models (LLMs) such as OpenAI’s GPT-4 (ChatGPT), Google Gemini, and Anthropic Claude, with practical experience in designing, optimizing, and deploying AI/ML workflows in production environments to drive business value and innovation.
The ideal candidate will quickly adapt to new technologies and a go-getter/hands-on engineer, with quantitative concepts and data. Willing to be in the on-call rotation.
The Expertise We’re Looking For
Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.) required.
-
The role is primarily Python based however we are very open to a strong Java or C# Engineer who is willing to cross-train and work with Python
-
Strong Experience in RDBMS and AWS
-
Experience with object orientated programming principles and Data Structures
-
Knowledge of Cloud computing concepts (AWS) and using CI/CD tools
-
6+ years of enterprise development and a desire to work on a fast-paced development team.
-
Ability to balance multiple tasks concurrently is required
-
Experience in planning, designing, leading, and executing technical solutions and improvements.
The Skills You Bring
-
You have a track record of engineering experience by processing large datasets and building scalable applications and Rapid Prototyping
-
You have a background with enterprise development and a consistent record rapidly bring projects from inception to delivery in ambitious timeframes.
-
You have solid experience in Object Oriented Programming
-
You have solid experience in developing custom Data Pipelines to extract data, map data, transform data, and to load data in various data stores like Oracle, Snowflake, S3, PL/SQL, and / or shared drives.
-
You have solid experience in Python or Java or C#, ideally also with experience of data structure libraries such as Pandas / Numpy
-
You are familiar with extracting data from REST APIs
-
Your demonstrable experience developing scripting in Linux and Windows
-
Experience with migrating applications to AWS (Cloud) will be an added advantage.
Click **'Apply Now'**to submit your application or send your resume directly to richard.riddett@cpl.ie
Interview prep pack
Grounded in this listing. Use it to prepare examples before you apply.
Your interview focus
Based on this listing, the Senior Data Engineer role on the AS&R Team focuses on designing and implementing scalable data solutions, leveraging cloud technologies, and processing large structured and unstructured datasets to support advanced analytics and AI/ML workflows.
- Hands-on technical leadership·High
- Cloud and data pipeline expertise·High
- Rapid prototyping and delivery·Medium
- AI/ML workflow exposure·Medium
Only have 30 minutes?
Follow a focused preparation plan based on this job.
Start 30-minute prep
Your 30-minute plan
Review Recent Data Engineering Projects
0–8 minSelect 2-3 projects that showcase your experience with scalable data pipelines, cloud migration, and rapid prototyping. Prepare concise STAR stories.
Refresh AWS and CI/CD Knowledge
8–15 minStudy AWS data services and CI/CD tools relevant to the role, focusing on practical applications and migration scenarios.
Practice Explaining OOP and Data Structures
15–20 minPrepare to discuss how you have applied object-oriented programming and data structures in data engineering contexts, using Python or Java.
Research LLMs and Prompt Engineering
20–25 minRead up on integrating large language models into data workflows and be ready to discuss potential applications.
Prepare Role-Specific Questions
25–30 minDraft and rehearse thoughtful questions about the team’s data sources, challenges, and AI/ML initiatives.
Talking points
, 6 itemsDesigning and Implementing Scalable Data Pipelines
You should be ready to discuss examples where you built or optimized data pipelines for large, complex datasets, as this is central to the role.
Cloud Migration and AWS Expertise
Prepare to share your experience migrating applications or data workflows to AWS, as cloud proficiency is a key requirement.
Object-Oriented Programming and Data Structures
Demonstrate your ability to apply OOP principles and data structures in real-world engineering projects, especially using Python, Java, or C#.
Rapid Prototyping and Agile Delivery
Showcase your ability to quickly bring projects from inception to delivery, highlighting your adaptability and hands-on approach.
Extracting and Transforming Data from APIs and Various Sources
Be prepared to discuss how you have extracted, mapped, and transformed data from REST APIs and other sources into data stores like Snowflake or S3.
Leading Technical Solutions and Team Collaboration
Provide examples of planning, designing, and leading technical solutions, as well as collaborating within fast-paced teams.
What to research
, 5 itemsReview AWS Data Services
Refresh your knowledge of AWS services relevant to data engineering, such as S3, EC2, Lambda, Glue, and Redshift.
Brush Up on Python, Java, and Data Structure Libraries
Prepare to discuss and demonstrate your experience with Python (and optionally Java or C#), focusing on OOP and libraries like Pandas and Numpy.
Understand Data Pipeline Architectures
Be ready to explain your approach to designing, building, and optimizing data pipelines for both structured and unstructured data.
Familiarize Yourself with CI/CD in Data Engineering
Review how CI/CD tools are used to automate testing and deployment of data workflows.
Research Prompt Engineering and LLM Integration
Explore recent trends and practical examples of integrating large language models (e.g., GPT-4) into data workflows.
Questions to ask
, 6 itemsWhat are the main data sources and types (structured/unstructured) the team currently works with?
Why ask this? Clarifies the technical landscape and helps you tailor your examples to their environment.
How does the team approach rapid prototyping and balancing innovation with production stability?
Why ask this? Shows your interest in their development process and readiness for a fast-paced environment.
What opportunities are there for hands-on involvement with AI/ML workflows and prompt engineering?
Why ask this? Demonstrates your enthusiasm for the AI/ML aspects of the role.
How is success measured for data engineering projects within the AS&R team?
Why ask this? Helps you understand performance expectations and key metrics.
What are the biggest technical challenges the team is currently facing?
Why ask this? Gives insight into where your skills can have the most impact.
How does the on-call rotation work, and what types of incidents are most common?
Why ask this? Clarifies expectations for support and operational responsibilities.
Register now to upload your CV
Create a free account, save a PDF or Word CV, and quick apply on roles that take applications here.