Data Engineer

Reperio Human Capital · Recruitment agency
Contract•Data engineering•€450-550/day (EUR)•Ireland · Remote within Ireland · Hybrid
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At a glance

Employment type
Contract
Workplace
Hybrid
Day rate
€450-550/day (EUR)

Technologies & skills

Cloud & infrastructure

TerraformAzureCI/CD

Other technical skills

SnowflakeDatabricksSQL

What you'll be doing

Contract Data Engineer role in Dublin (hybrid, 6 months) supporting business, finance, and analytics in a regulated environment. Focus on designing, developing, and optimizing data pipelines and ETL processes using Azure and SQL. Collaborate with stakeholders to improve data quality, governance, and reporting.

  • Design, develop, and optimize robust data pipelines, ETL processes, and scalable data solutions using Microsoft Azure and SQL
  • Work closely with technical and business stakeholders to improve data quality, governance, reporting, and data-driven processes

Key requirements

Must-have

  • Previous experience in a Data Engineering role
  • Technical experience with Azure, particularly Azure SQL, MSSQL, Azure Data Factory, Data Lake/Blob Storage, and Synapse
  • Advanced SQL and data modelling skills
  • Strong understanding of ETL, data pipelines, data quality, governance, security, and performance optimisation
  • Experience with Agile delivery and CI/CD
  • Experience working with multiple stakeholders and translating business requirements into technical data solutions

Nice-to-have

  • Experience with Snowflake or Databricks
  • Experience with modern cloud data platforms and distributed data processing
  • Experience supporting finance, regulatory, compliance, risk, privacy, or security data initiatives
  • Experience with Power BI/SAS, Azure DevOps, GitHub, Terraform or similar tooling
  • Knowledge of financial services regulations and data governance frameworks

Role signals

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

Full job description

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

About the Role

  • Join a large-scale data engineering team supporting business, finance and analytics functions within a regulated environment.

  • Design, develop and optimise robust data pipelines, ETL processes and scalable data solutions using Microsoft Azure and SQL.

  • Work closely with technical and business stakeholders to improve data quality, governance, reporting and data-driven processes.

Requirements

  • Previous experience in a Data Engineering role

  • Previous technical experience with Azure, particularly Azure SQL, MSSQL, Azure Data Factory, Data Lake/Blob Storage and Synapse, with advanced SQL and data modelling skills.

  • Strong understanding of ETL, data pipelines, data quality, governance, security and performance optimisation, alongside experience with Agile delivery and CI/CD.

  • Experience working with multiple stakeholders and translating business requirements into robust technical data solutions.

Desirable

  • Previous experience with Snowflake or Databricks, including modern cloud data platforms and distributed data processing.

  • Previous experience supporting finance, regulatory, compliance, risk, privacy or security data initiatives.

  • Experience with Power BI/SAS, Azure DevOps, GitHub, Terraform or similar tooling.

  • Knowledge of financial services regulations and data governance frameworks

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 hands-on Data Engineer contract in Dublin, focused on designing and optimizing data pipelines and ETL processes using Azure technologies, with an emphasis on data quality, governance, and collaboration with stakeholders in a regulated environment.

  • Azure Data Engineering Expertise·High
  • ETL and Data Pipeline Design·High
  • Data Governance and Quality·Medium
  • Stakeholder Collaboration·Medium

Only have 30 minutes?

Follow a focused preparation plan based on this job.

Start 30-minute prep

Your 30-minute plan

  1. Review Azure Data Engineering Tools

    0–8 min

    Refresh your knowledge and prepare examples involving Azure SQL, Data Factory, Synapse, and Data Lake/Blob Storage.

  2. Prepare STAR Stories for Key Projects

    8–15 min

    Select 2-3 relevant projects that showcase your skills in ETL, data quality, and stakeholder collaboration, and structure them using the STAR method.

  3. Brush Up on Data Governance and Compliance

    15–20 min

    Review frameworks and best practices for data quality, governance, and security, especially in regulated environments.

  4. Revisit CI/CD and Agile Practices

    20–25 min

    Prepare to discuss your experience with CI/CD pipelines, version control, and Agile delivery in data engineering.

  5. Draft Role-Specific Questions

    25–30 min

    Prepare thoughtful questions about the team, challenges, and technologies 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

  • Designing and Optimising Data Pipelines on Azure

    You should be ready to discuss specific examples of building and improving data pipelines using Azure services, as this is central to the role.

  • Advanced SQL and Data Modelling

    Demonstrating your ability to write complex SQL queries and design scalable data models will show your technical depth.

  • Implementing Data Quality and Governance

    Prepare to explain how you have ensured data quality, compliance, and governance in previous projects, especially in regulated environments.

  • Translating Business Requirements into Technical Solutions

    You will need to show how you have worked with stakeholders to understand business needs and deliver robust data solutions.

  • CI/CD and Agile Delivery in Data Engineering

    Be ready to discuss your experience with continuous integration, deployment, and Agile methodologies in the context of data engineering.

What to research

, 4 items

  • Azure Data Engineering Services

    Review your experience and knowledge of Azure SQL, Data Factory, Synapse, Data Lake/Blob Storage, and how they integrate in data pipelines.

  • ETL and Data Pipeline Best Practices

    Prepare examples of designing, optimising, and troubleshooting ETL processes, focusing on scalability and performance.

  • Data Quality, Governance, and Security

    Refresh your understanding of data governance frameworks, quality assurance, and security practices, especially in regulated industries.

  • CI/CD and Agile in Data Engineering

    Be ready to discuss your experience with CI/CD pipelines, version control, and Agile delivery in data projects.

Questions to ask

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

    Why ask this? To clarify the technical environment and assess alignment with your experience.

  2. How does the team approach data governance and compliance, especially given the regulated environment?

    Why ask this? To understand the importance and implementation of governance frameworks in the role.

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

    Why ask this? To identify key pain points and areas where you can add value.

  4. How are business requirements typically gathered and prioritised for data engineering projects?

    Why ask this? To learn about stakeholder engagement and project workflow.

  5. What does success look like for this role over the initial 6-month contract?

    Why ask this? To set clear expectations and understand deliverables.

  6. Is there an opportunity to work with or learn Snowflake, Databricks, or other modern data platforms?

    Why ask this? To gauge opportunities for skill development and exposure to new technologies.

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Apply NowApply before: 30 Oct 2026