Data Engineer

Reperio Human Capital · Recruitment agency
Contract•Data engineering•€500-550/day (EUR)•Ireland · Remote within Ireland · Hybrid
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At a glance

Employment type
Contract
Workplace
Hybrid
Day rate
€500-550/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 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 for a Data Engineer on a 12-month contract in Dublin, focusing on designing, building, and delivering scalable data solutions using Azure, Databricks, SQL, and related technologies within a hybrid work environment.

  • Cloud Data Engineering Experience·High
  • Distributed Data Pipeline Design·High
  • SQL Proficiency·High
  • Leadership and Mentoring·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 role and the technologies used.

  2. Refresh Azure and Databricks Knowledge

    8–15 min

    Revisit key features, services, and best practices for data engineering on Azure and Databricks.

  3. Practice Explaining SQL Solutions

    15–20 min

    Prepare to discuss complex SQL queries and optimizations you have implemented in production environments.

  4. Prepare Examples of Ensuring Reliability and Security

    20–25 min

    Think through specific instances where you improved reliability, security, or maintainability in data solutions.

  5. Draft Questions for the Interviewer

    25–30 min

    Write down 3-4 thoughtful questions about the team, challenges, and technical environment.

Likely questions

, 7 items

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

Talking points

, 6 items

  • Translating Architectural Designs

    Be ready to discuss how you have interpreted high-level architectural plans into detailed, scalable engineering solutions, as this is a core responsibility.

  • Building Distributed Data Pipelines

    Prepare examples of designing and implementing robust, distributed data pipelines, especially using cloud platforms and big data tools.

  • Hands-on Experience with Azure and Databricks

    Demonstrate your practical experience with Azure and Databricks, including how you leveraged these platforms for data engineering tasks.

  • Ensuring Reliability, Security, and Performance

    Showcase how you have delivered solutions that are reliable, secure, high-performing, and maintainable, as these are explicitly required.

  • SQL and Data Processing Skills

    Be prepared to discuss your proficiency with SQL and how you have used it in large-scale data engineering projects.

  • Mentoring and Leading Technical Delivery

    If applicable, provide examples of mentoring other engineers or leading technical workstreams, as leadership is a desirable skill.

What to research

, 4 items

  • Azure and Databricks Ecosystem

    Review your experience with Azure and Databricks, focusing on data pipeline development, orchestration, and optimization.

  • Distributed Data Pipeline Design

    Prepare to discuss end-to-end design and implementation of scalable, distributed data pipelines, including challenges and solutions.

  • SQL for Data Engineering

    Refresh your knowledge of advanced SQL, especially in the context of large-scale data processing and optimization.

  • Production-Ready Data Solutions

    Be ready to explain how you ensure reliability, security, and maintainability in your data engineering projects.

Questions to ask

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

    Why ask this? Clarifies the technical environment and helps you tailor your examples.

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

    Why ask this? Helps you understand performance expectations and priorities.

  3. Can you describe the team structure and how data engineers collaborate with architects and other stakeholders?

    Why ask this? Provides insight into collaboration and reporting lines.

  4. What are the biggest technical challenges the team is currently facing?

    Why ask this? Shows your interest in problem-solving and readiness to contribute.

  5. Is there an opportunity to mentor junior engineers or lead technical workstreams?

    Why ask this? Clarifies expectations around leadership and growth opportunities.

  6. How does the team approach CI/CD and automation for data pipelines?

    Why ask this? Demonstrates your interest in best practices and process improvement.

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Apply NowApply before: 30 Nov 2026