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

PythonJavaScala

Cloud & infrastructure

AWSAzure

Other technical skills

SnowflakeRedshiftSQL

Secondary technologies

dbt

What you'll be doing

Contract Data Engineer role in Dublin (hybrid, 6 months). Focus on designing scalable data pipelines, automation for analytics, integrating data from multiple sources, and data modeling. Requires strong SQL, Python, and experience with Java/Scala. Cloud and modern data platform experience desirable.

  • Designing and developing scalable data pipelines and data processing solutions
  • Developing automation processes for data engineering and analytics deployments
  • Transforming and integrating data from multiple sources, including legacy systems
  • Designing data models, architectures and data flows

Key requirements

Must-have

  • Previous experience in a Data Engineering role
  • Advanced SQL skills
  • Strong experience with relational and non-relational databases
  • Experience designing and implementing ETL/ELT, data warehousing and data modelling solutions
  • Hands-on experience with Python
  • Experience with Java, Scala or similar languages

Nice-to-have

  • Experience with dbt
  • Knowledge of DevOps practices and tooling
  • Experience working with major cloud platforms such as Azure, AWS or GCP
  • Proficiency with modern data platforms such as Snowflake, Synapse, Redshift, Vertica or Hadoop

Role signals

Technical focus
data engineering
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 6-month contract, focusing on hybrid working. Strong day rate available.

About the Role

  • Designing and developing scalable data pipelines and data processing solutions.

  • Developing automation processes for data engineering and analytics deployments.

  • Transforming and integrating data from multiple sources, including legacy systems.

  • Designing data models, architectures and data flows.

Requirements

  • Previous experience in a Data Engineering role.

  • Advanced SQL skills and strong experience with relational and non-relational databases.

  • Strong experience designing and implementing ETL/ELT, data warehousing and data modelling solutions.

  • Hands-on experience with Python and experience with Java, Scala or similar languages.

Desirable

  • Experience with dbt.

  • Knowledge of DevOps practices and tooling.

  • Experience working with major cloud platforms such as Azure, AWS or GCP.

  • Proficiency with modern data platforms such as Snowflake, Synapse, Redshift, Vertica or Hadoop.

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 focuses on designing and developing scalable data pipelines, integrating data from multiple sources, and implementing automation for analytics deployments using modern data platforms and programming languages.

  • Hands-on data engineering experience·High
  • Advanced SQL and database skills·High
  • Cloud and modern data platform proficiency·Medium
  • Programming in Python and JVM languages·High

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 summarize your most relevant data pipeline, ETL/ELT, and data integration projects, focusing on challenges and outcomes.

  2. Practice Advanced SQL and Data Modeling

    8–15 min

    Work through complex SQL queries and review data modeling concepts relevant to both relational and non-relational databases.

  3. Refresh Programming Skills in Python and JVM Languages

    15–20 min

    Review code samples and be ready to discuss or demonstrate your experience with Python and either Java or Scala.

  4. Research Cloud and Modern Data Platforms

    20–25 min

    Review your experience with AWS, Azure, Snowflake, and Redshift, and prepare to discuss specific use cases.

  5. Prepare Questions and Review Role Requirements

    25–30 min

    Draft thoughtful questions for the interviewer and ensure you can clearly articulate how your experience matches the listed requirements.

Likely questions

, 6 items

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

Talking points

, 6 items

  • Designing Scalable Data Pipelines

    Be ready to discuss how you have architected and built robust data pipelines, especially those handling large or complex data sets.

  • ETL/ELT and Data Warehousing Solutions

    Prepare examples of your experience designing and implementing ETL/ELT processes and building or maintaining data warehouses.

  • Advanced SQL and Database Skills

    Demonstrate your proficiency with both relational and non-relational databases, including writing complex SQL queries and optimizing performance.

  • Programming in Python, Java, or Scala

    Showcase your hands-on experience with Python and at least one JVM language, focusing on how you have used them in data engineering contexts.

  • Integrating Data from Multiple and Legacy Sources

    Share examples where you have successfully integrated disparate data sources, including legacy systems, into unified data models or pipelines.

  • Cloud Platforms and Modern Data Tools

    Highlight your experience with cloud services (AWS, Azure) and modern data platforms (Snowflake, Redshift), especially in production environments.

What to research

, 5 items

  • Review Data Pipeline Projects

    Prepare detailed examples of data pipelines you have designed and implemented, focusing on scalability and integration.

  • Brush Up on Advanced SQL

    Practice writing and optimizing complex SQL queries, including those for both relational and non-relational databases.

  • Refresh Knowledge of ETL/ELT and Data Warehousing

    Review your experience with ETL/ELT tools, data warehousing concepts, and data modeling best practices.

  • Demonstrate Programming Skills

    Be ready to discuss and possibly demonstrate your proficiency in Python and at least one JVM language (Java or Scala).

  • Understand Cloud and Modern Data Platforms

    Review your hands-on experience with cloud platforms (AWS, Azure) and modern data tools (Snowflake, Redshift).

Questions to ask

, 6 items
  1. What are the main data platforms and tools currently in use for this project?

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

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

    Why ask this? Shows your interest in problem-solving and understanding of the team's priorities.

  3. How is success measured for this role and for data engineering projects in general?

    Why ask this? Helps you understand expectations and how your performance will be evaluated.

  4. What is the typical workflow for deploying and maintaining data pipelines here?

    Why ask this? Gives insight into automation, DevOps practices, and operational maturity.

  5. How does the team handle data integration from legacy systems?

    Why ask this? Shows your awareness of integration challenges and interest in best practices.

  6. Are there opportunities to contribute to architectural decisions or process improvements?

    Why ask this? Demonstrates your interest in adding value beyond hands-on development.

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Apply NowApply before: 26 Oct 2026