Data Engineer

Reperio Human Capital · Recruitment agency
Contract•Data engineering•€400-450/day (EUR)•Ireland · Remote within Ireland · Hybrid
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At a glance

Employment type
Contract
Workplace
Hybrid
Day rate
€400-450/day (EUR)

Technologies & skills

Primary technologies

Python

Cloud & infrastructure

AzureCI/CD

Other technical skills

DatabricksSQLSpark

What you'll be doing

12-month hybrid contract Data Engineer role in Dublin, Ireland. Responsible for translating architectural designs into scalable solutions, owning engineering workstreams, and ensuring reliability, security, and maintainability. Requires experience with modern cloud data platforms, SQL, and building distributed data pipelines.

  • Translate architectural designs into scalable, production-ready solutions
  • Own key engineering workstreams from design through to delivery
  • Ensure solutions are reliable, secure, high-performing and maintainable

Key requirements

Must-have

  • Strong commercial experience delivering data engineering solutions within modern cloud data platforms
  • Proficiency with SQL
  • Proven experience designing and building scalable, distributed data pipelines
  • Hands-on experience with Azure, Databricks or equivalent cloud technologies

Nice-to-have

  • Technical experience with Databricks, Spark or Python
  • Experience with Delta Lake and Lakehouse architectures
  • Knowledge of CI/CD, DevOps and automation practices
  • Experience leading technical delivery and mentoring Data Engineers

Role signals

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

Full job description

I'm currently recruiting for a Data Engineer based in Dublin, this is an initial 12-month contract. Focusing on hybrid working, strong day rate available.

About the role

  • Translate architectural designs into scalable, production-ready solutions.

  • Own key engineering workstreams from design through to delivery.

  • Ensure solutions are reliable, secure, high-performing and maintainable.

Requirements

  • Strong commercial experience delivering data engineering solutions within modern cloud data platforms.

  • Proficiency with SQL

  • Proven experience designing and building scalable, distributed data pipelines.

  • Hands-on experience with Azure, Databricks or equivalent cloud technologies.

Desirable

  • Previous technical experience with Databricks, Spark or Python

  • Experience with Delta Lake and Lakehouse architectures.

  • Knowledge of CI/CD, DevOps and automation practices.

  • Experience leading technical delivery and mentoring Data Engineers.

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 role is a contract Data Engineer position in Ireland focused on designing, building, and delivering scalable data solutions using modern cloud platforms, particularly Azure and Databricks, with a strong emphasis on SQL and distributed data pipelines.

  • Hands-on experience with Azure and Databricks·High
  • Ability to design and deliver scalable data pipelines·High
  • Proficiency in SQL and distributed data processing·High
  • Understanding of CI/CD and automation·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review Recent Data Engineering Projects

    0–8 min

    Select 1-2 relevant projects where you designed and delivered scalable data pipelines, focusing on your use of Azure, Databricks, or similar platforms.

  2. Brush Up on SQL and Distributed Data Processing

    8–14 min

    Practice explaining complex SQL queries and optimizations, especially in distributed or cloud environments.

  3. Study CI/CD and Automation Practices

    14–20 min

    Prepare to discuss your experience with CI/CD pipelines and automation in data engineering contexts.

  4. Prepare Examples of Ensuring Reliability and Security

    20–25 min

    Think of specific instances where you improved solution reliability, security, or maintainability.

  5. Draft Role-Specific Questions

    25–30 min

    Write down 2-3 thoughtful questions about the team, technology stack, and project challenges to ask during the interview.

Likely questions

, 6 items

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

Talking points

, 5 items

  • Translating Architectural Designs to Production Solutions

    You will need to demonstrate your ability to interpret high-level designs and implement them as robust, scalable data systems.

  • Building and Maintaining Distributed Data Pipelines

    The role requires hands-on experience in designing and delivering data pipelines that can handle large-scale, distributed workloads.

  • Expertise in Azure and Databricks

    You should be able to discuss your practical experience with these platforms, including how you leverage their features for data engineering tasks.

  • Ensuring Solution Reliability, Security, and Performance

    Be prepared to explain how you ensure that your data solutions are robust, secure, and maintainable in a production environment.

  • CI/CD and Automation in Data Engineering

    Familiarity with DevOps practices and automation is desirable, so be ready to discuss any relevant experience.

What to research

, 4 items

  • Azure and Databricks Platform Features

    Review the core services, data processing capabilities, and integration points of Azure and Databricks.

  • Design Patterns for Scalable Data Pipelines

    Refresh your knowledge of best practices for building distributed, high-performance data pipelines.

  • SQL Optimization Techniques

    Prepare examples of complex SQL queries and performance tuning in large-scale environments.

  • CI/CD and Automation Tools for Data Engineering

    Familiarize yourself with common CI/CD tools and how they are applied in data engineering workflows.

Questions to ask

, 6 items
  1. What are the main data platforms and tools currently in use by the team?

    Why ask this? To understand the technical environment and align your experience with their stack.

  2. How is success measured for data engineering projects in this role?

    Why ask this? To clarify expectations and key performance indicators.

  3. Can you describe the typical workflow from architectural design to production deployment?

    Why ask this? To gain insight into the team's processes and your potential responsibilities.

  4. What opportunities exist for mentoring or leading within the data engineering team?

    Why ask this? To assess the scope for leadership and professional growth.

  5. How does the team approach solution reliability, security, and maintainability?

    Why ask this? To understand the standards and practices you will be expected to uphold.

  6. What are the biggest challenges currently facing the data engineering team?

    Why ask this? To identify areas where your skills can add immediate value.

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Apply NowApply before: 26 Oct 2026