Senior Data Analytics Engineer

Reperio Human Capital · Recruitment agency

Contract•Data engineering•€450-500/day (EUR)•Ireland · Remote within Ireland · Hybrid

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TechJobs.ie Job Insights

At a glance

Employment type: Contract
Location: Ireland · Remote within Ireland · Hybrid
Workplace: Hybrid
Day rate: €450-500/day (EUR)
Category: Data engineering

Technologies & skills

Primary technologies

Python .NET C#

Cloud & infrastructure

Azure

Other technical skills

Databricks SQL

What you'll be doing

Senior Data Analytics Engineer (6-month contract, hybrid in Ireland) to lead data architecture across client projects using Microsoft data and cloud tools. Responsibilities include owning data architecture, building solutions with Azure SQL, Databricks, .NET/C#, and working through the project lifecycle.

Own the data architecture of applications from design through to delivery
Build solutions with Azure SQL, Azure Databricks, .NET/C#, and Power BI / Microsoft Fabric
Work across the whole project lifecycle, including requirements gathering, development, and training end users

Key requirements

Must-have

Previous experience in a data engineering role
Proficiency in Python, SQL, and .NET/C#
Solid grasp of database design for both transactional (OLTP) and analytical (OLAP) systems

Nice-to-have

Proficiency with Azure Databricks / PySpark
Previous experience building and deploying ML or AI solutions in Azure
Previous technical experience with Power BI or Microsoft Fabric

Role signals

Technical focus: data engineering
Architecture / system design: Indicated in the listing
Hands-on vs management: Hands-on

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Full job description

I'm currently recruiting for a Senior Data Analytics Engineer based in Dublin. This is an initial 6-month contract, focusing on hybrid working. Strong day rate available.

A chance to lead data architecture across a range of client projects, using the latest Microsoft data and cloud tools, with a well-established software consultancy.

About the Role

Own the data architecture of the applications you work on, from design through to delivery.
Build solutions with Azure SQL, Azure Databricks, .NET/C# and Power BI / Microsoft Fabric.
Work across the whole project lifecycle, including requirements gathering, development and training end users.

Requirements

Previous experience in a data engineering role
Proficiency in Python, SQL and NET/C#
Solid grasp of database design for both transactional (OLTP) and analytical (OLAP) systems

Desirable

Proficiency with Azure Databricks / PySpark
Previous experience building and deploying ML or AI solutions in Azure
Previous technical experience with Power BI or Microsoft Fabric

If this role sounds of interest to you then apply through the link provided below.

Reperio Human Capital acts as an Employment Agency and an Employment Business.

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 Analytics Engineer contract role in Ireland emphasizes end-to-end data architecture leadership, hands-on development with Microsoft cloud tools, and expertise in Python, SQL, and .NET/C# within a consultancy environment.

Data architecture leadership·High
Hands-on technical expertise·High
Cloud and Microsoft stack proficiency·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 Architecture Projects
0–7 min
Select 1-2 projects where you led data architecture from design to delivery, and prepare concise summaries.
Refresh Technical Skills in Python, SQL, and .NET/C#
7–14 min
Practice explaining your use of these languages in data engineering scenarios, focusing on integration and optimization.
Study Azure SQL, Databricks, and Power BI/Microsoft Fabric
14–20 min
Review documentation and your experience with these tools, noting any recent updates or best practices.
Prepare Examples of OLTP and OLAP Database Design
20–25 min
Be ready to discuss your approach and provide concrete examples of both types of systems.
Plan Questions for the Interviewer
25–30 min
Select 2-3 questions from the provided list that align with your interests and priorities.

Likely questions

Expand all

Priority reflects how strongly this topic is emphasised in the job listing, not whether it will be asked.

1Can you describe a project where you owned the data architecture from design through to delivery?High
Why they may ask
Assesses your ability to take responsibility for end-to-end architecture and deliver results.
Prepare to discuss
- Clearly outline the project scope and your specific responsibilities.
- Explain key architectural decisions and their impact.
- Discuss challenges faced and how you overcame them.
- Highlight collaboration with stakeholders and successful delivery.
Tip: Use a recent, relevant example and quantify outcomes where possible.
2How have you used Python, SQL, and .NET/C# in your previous data engineering roles?High
Why they may ask
Evaluates your technical proficiency with the core languages required for the role.
Prepare to discuss
- Describe specific tasks or projects involving each language.
- Explain why you chose each technology for the task.
- Highlight any integration or performance considerations.
- Mention any automation or efficiency improvements you implemented.
Tip: Be ready to discuss both breadth and depth of your experience.
3What is your approach to designing databases for both OLTP and OLAP workloads?High
Why they may ask
Tests your understanding of database design principles for different use cases.
Prepare to discuss
- Explain the key differences between OLTP and OLAP systems.
- Discuss normalization, denormalization, and schema design choices.
- Provide examples of how you optimized for performance and scalability.
- Mention any tools or methodologies you used.
Tip: Use concrete examples to illustrate your approach.
4Describe your experience with Azure Databricks or PySpark.Medium
Why they may ask
Assesses your familiarity with cloud-based big data tools, which are desirable for the role.
Prepare to discuss
- Detail specific projects where you used Databricks or PySpark.
- Explain the data processing challenges and how you addressed them.
- Discuss integration with other Azure services.
- Highlight any performance tuning or cost optimization steps.
Tip: If you lack direct experience, relate similar technologies and your ability to learn quickly.
5How do you ensure effective communication and training for end users during project delivery?Medium
Why they may ask
Evaluates your ability to engage with stakeholders and support adoption of solutions.
Prepare to discuss
- Describe your process for gathering requirements and understanding user needs.
- Explain how you tailor communication for technical and non-technical audiences.
- Share examples of training materials or sessions you delivered.
- Discuss feedback mechanisms and continuous improvement.
Tip: Emphasize empathy and adaptability in your communication style.
6Have you built or deployed any ML or AI solutions in Azure?Lower
Why they may ask
Explores your experience with advanced analytics and cloud deployment, which is desirable for the role.
Prepare to discuss
- Describe the business problem and the ML/AI solution implemented.
- Explain your role in model development, deployment, and monitoring.
- Discuss integration with Azure services and any challenges faced.
- Highlight measurable outcomes or improvements.
Tip: If you have limited experience, focus on your understanding of the process and willingness to learn.
7What strategies do you use to keep up with the latest Microsoft data and cloud tools?Lower
Why they may ask
Assesses your commitment to continuous learning in a rapidly evolving tech landscape.
Prepare to discuss
- Mention specific resources, communities, or certifications.
- Describe how you apply new knowledge to your work.
- Share examples of recent tools or features you adopted.
- Highlight your proactive approach to professional development.
Tip: Be specific about your learning habits and recent achievements.

Talking points

End-to-End Data Architecture Ownership
You will be expected to lead the design and delivery of data solutions, so prepare examples where you owned architecture decisions and saw projects through to completion.
Technical Proficiency in Python, SQL, and .NET/C#
Demonstrating hands-on experience with these languages is crucial, as they are core to the role's daily responsibilities.
Experience with Azure SQL and Databricks
The role requires building solutions using these platforms; be ready to discuss specific projects and technical challenges you addressed.
Database Design for OLTP and OLAP
A solid grasp of both transactional and analytical database systems is required, so prepare to explain your design choices and optimization strategies.
Project Lifecycle and Stakeholder Engagement
You will work across requirements gathering, development, and user training; highlight your communication and collaboration skills with clients or end users.

What to research

Review Azure SQL and Databricks Capabilities
Refresh your knowledge of Azure SQL and Databricks, focusing on architecture, integration, and common use cases.
Brush Up on Python, SQL, and .NET/C# Skills
Prepare to discuss and demonstrate your experience with these languages in data engineering contexts.
Understand OLTP vs OLAP Database Design
Be ready to explain and provide examples of designing databases for both transactional and analytical workloads.
Familiarize with Power BI and Microsoft Fabric
Review your experience or knowledge of these tools, as they are part of the solution stack.

Questions to ask

What types of client projects will I be working on, and what are their typical data challenges?
Why ask this? To understand the business context and technical complexity of the work.
How is the data architecture team structured, and what level of autonomy will I have?
Why ask this? To clarify your responsibilities and decision-making authority.
What is the typical project lifecycle, and how are requirements gathered from clients?
Why ask this? To assess the consultancy's approach to project management and stakeholder engagement.
Which Azure services and tools are most commonly used across your projects?
Why ask this? To gauge the technical environment and identify areas for upskilling.
What support is available for professional development and staying current with Microsoft data technologies?
Why ask this? To understand opportunities for growth and learning.
How is success measured for this role, both technically and in terms of client satisfaction?
Why ask this? To clarify performance expectations and key deliverables.

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Apply NowApply before: 9 Nov 2026

Senior Data Analytics Engineer

TechJobs.ie Job Insights

At a glance

Technologies & skills

What you'll be doing

Key requirements

Role signals

Similar jobs

Full job description

Interview prep pack

Your interview focus

Only have 30 minutes?

Your 30-minute plan

Likely questions

Talking points

What to research

Questions to ask

Register now to upload your CV

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