Data Engineer

CPL · Recruitment agency
Full-time•Data engineering•Dublin, Ireland · Remote within Ireland · Hybrid
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At a glance

Employment type
Full-time
Workplace
Hybrid · 3 days in office

Technologies & skills

Primary technologies

PythonGo

Other technical skills

DatabricksSQL

Secondary technologies

REST APIs

What you'll be doing

Join a Dublin-based technology company as a Data Engineer, designing and maintaining data platforms, pipelines, and integrations for analytics and AI-driven solutions. Collaborate with engineering, AI/ML, and DevOps teams to deliver scalable, high-quality data assets in a hybrid work environment.

  • Designing and maintaining scalable ETL/ELT and data ingestion pipelines
  • Transforming structured, semi-structured, and unstructured data into high-quality datasets
  • Developing data models, validation frameworks, and quality controls
  • Integrating data from APIs, cloud platforms, internal systems, and third-party sources
  • Supporting data governance, security, compliance, and documentation standards
  • Collaborating with cross-functional engineering and data teams to ensure reliable data availability

Key requirements

Must-have

  • 2-3 years experience in a similar role
  • Strong commercial experience in Data Engineering
  • Advanced SQL and Python development skills
  • Expertise in data ingestion, transformation, data modelling, and pipeline optimisation
  • Experience working with APIs, cloud-based data environments, data warehouses, or lakehouses
  • Exposure to workflow orchestration and systems integration
  • Understanding of data governance, security, privacy, and compliance best practices
  • Irish/EU Citizenship

Nice-to-have

  • Knowledge of Databricks
  • Experience with Go (Golang)

Experience: 2-3 years

Role signals

Technical focus
data engineering
Hands-on vs management
Hands-on

Full job description

Data Engineer

Dublin | Hybrid (3 days per week)

  • Cpl are partnering with an innovative and rapidly growing technology organisation to hire a Data Engineer for their Dublin-based team.
  • This is an exciting opportunity to join a high-performing engineering environment where data is at the heart of product development, analytics, and AI-driven solutions.
  • The successful candidate will play a key role in designing and maintaining the data platforms, pipelines, and integrations that power critical business applications.
  • Working closely with software engineers, AI/ML specialists, and DevOps teams, you will help transform complex datasets into trusted, scalable, and actionable data assets.

The Role

As a Data Engineer, you will be responsible for building and supporting robust data infrastructure that enables advanced analytics, reporting, and machine learning initiatives.

  • Key responsibilities include:

  • Designing and maintaining scalable ETL/ELT and data ingestion pipelines.

  • Transforming structured, semi-structured, and unstructured data into high-quality datasets.

  • Developing data models, validation frameworks, and quality controls.

  • Integrating data from APIs, cloud platforms, internal systems, and third-party sources.

  • Supporting data governance, security, compliance, and documentation standards.

  • Collaborating with cross-functional engineering and data teams to ensure reliable data availability across business-critical platforms.

Skills & Experience

  • We are looking for candidates with:

  • 2-3 Years experience in a similar role

  • Strong commercial experience in Data Engineering.

  • Advanced SQL and Python development skills.

  • Expertise in data ingestion, transformation, data modelling, and pipeline optimisation.

  • Experience working with APIs, cloud-based data environments, data warehouses, or lakehouses.

  • Exposure to workflow orchestration and systems integration.

  • Knowledge of Databricks would be advantageous.

  • Experience with Go (Golang) is beneficial but not essential.

  • Understanding of data governance, security, privacy, and compliance best practices.

  • Must have Irish/EU Citizenship

What's on Offer

  • Opportunity to work on a modern data platform supporting AI and analytics initiatives.
  • Exposure to cutting-edge technology and large-scale data challenges.
  • Collaborative engineering culture with strong cross-functional engagement.
  • Hybrid working model based in Dublin.
  • Significant opportunities for learning, growth, and career progression within a scaling technology organisation.

Key Technologies

  • Python
  • SQL
  • Go (Golang)
  • APIs & Integrations
  • Cloud Data Platforms
  • ETL / ELT
  • Data Modelling
  • Databricks (desirable
    #LI-JM2

Interview prep pack

Grounded in this listing. Use it to prepare examples before you apply.

Your interview focus

Based on this listing, the Data Engineer role in Dublin focuses on building and maintaining robust data pipelines, integrating diverse data sources, and supporting analytics and AI initiatives within a collaborative, cross-functional engineering environment.

  • Hands-on data engineering experience·High
  • Advanced SQL and Python proficiency·High
  • Data pipeline and integration expertise·High
  • Understanding of data governance and compliance·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review and Document Key Data Engineering Projects

    0–8 min

    List and summarise your most relevant projects, focusing on pipeline design, data modelling, and integration.

  2. Practice Explaining Technical Solutions

    8–15 min

    Rehearse clear, concise explanations of your use of SQL, Python, and any experience with Databricks or Go.

  3. Refresh Knowledge of Data Governance and Compliance

    15–20 min

    Review best practices and prepare examples of how you have implemented governance, security, and compliance.

  4. Prepare Questions for the Interviewers

    20–25 min

    Select and tailor questions to ask about the team, technology stack, and growth opportunities.

  5. Research the Organisation and Team Structure

    25–30 min

    Look up public information about the company’s technology focus and team setup to contextualise your answers.

Likely questions

, 8 items

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

Talking points

, 6 items

  • Designing and Optimising ETL/ELT Pipelines

    You should be ready to discuss your experience building scalable, reliable data pipelines, as this is central to the role.

  • Advanced SQL and Python Skills

    Demonstrating strong coding ability in SQL and Python is essential, as these are core technologies for the position.

  • Data Modelling and Quality Controls

    Be prepared to explain how you have developed data models and implemented validation frameworks to ensure data quality.

  • Integrating APIs and Cloud Data Platforms

    The role requires integrating data from various sources, so examples of API and cloud platform integration will be valuable.

  • Data Governance and Compliance

    You should be able to discuss your understanding and practical application of data governance, security, and compliance best practices.

  • Collaboration with Cross-functional Teams

    Highlighting your experience working with software engineers, AI/ML specialists, and DevOps teams will show your ability to operate in a collaborative environment.

What to research

, 4 items

  • Review ETL/ELT Pipeline Projects

    Prepare detailed examples of your work designing, building, and optimising data pipelines, including technologies used and outcomes.

  • Brush Up on Advanced SQL and Python

    Refresh your knowledge of advanced SQL queries, Python scripting for data engineering, and relevant libraries or frameworks.

  • Understand Data Governance and Compliance

    Be ready to discuss your experience with data governance, security, privacy, and compliance best practices in previous roles.

  • Familiarise Yourself with Databricks and Go

    If you have experience, prepare examples; if not, review the basics and be ready to discuss how you would approach learning them.

Questions to ask

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

    Why ask this? To understand the technical environment and where your skills will be most applicable.

  2. How does the team approach data governance, security, and compliance?

    Why ask this? To clarify expectations and processes around critical data management responsibilities.

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

    Why ask this? To identify key priorities and areas where you can add immediate value.

  4. How does the data engineering team collaborate with AI/ML specialists and DevOps?

    Why ask this? To learn about cross-functional workflows and communication practices.

  5. What opportunities are there for learning and professional growth within the team?

    Why ask this? To assess the potential for skill development and career progression.

  6. How is success measured for data engineering projects in this organisation?

    Why ask this? To understand performance expectations and how your contributions will be evaluated.

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Apply NowApply before: 8 Nov 2026