Lead Data Engineer

Reperio Human Capital · Recruitment agency
Contract•Data engineering•€450-500/day (EUR)•Ireland · Remote within Ireland · Hybrid
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At a glance

Employment type
Contract
Workplace
Hybrid
Day rate
€450-500/day (EUR)

Technologies & skills

Cloud & infrastructure

TerraformAWSCI/CD

Other technical skills

SnowflakeSQLKafka

What you'll be doing

Lead Data Engineer (12-month contract, hybrid in Galway, Ireland) to design data models, build cloud pipelines, and modernise a large analytics platform. Requires strong SQL, Snowflake, AWS, data modelling, and experience with CI/CD and automated testing.

  • Design data models
  • Build cloud data pipelines
  • Collaborate with technical and business stakeholders
  • Modernise a large analytics platform for reporting, forecasting, and planning
  • Build and maintain production data pipelines

Key requirements

Must-have

  • Experience in Data Engineering, Analytics Engineering, or Data Platform Engineering
  • Strong data modelling (conceptual, logical, physical, dimensional)
  • Proficiency in SQL
  • Technical experience with Snowflake and AWS
  • Experience building and maintaining production data pipelines
  • Knowledge of data warehousing and modern data architectures
  • Experience with Git, CI/CD, and automated testing
  • Understanding of data quality, governance, security, and monitoring

Nice-to-have

  • Experience with real-time streaming or event-driven pipelines (Kafka or Kinesis)
  • Terraform or another Infrastructure-as-Code tool
  • Experience in financial services or regulated industry
  • Knowledge of Snowflake features (Snowpipe, Streams, Tasks, Dynamic Tables)

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 lead data engineer based in Galway. This is an initial 12-month contract, focusing on hybrid working. Strong day rate available.

About the Role

  • Design data models, build cloud pipelines

  • Collaborate with technical and business stakeholders

  • Help modernise a large analytics platform used for reporting, forecasting and planning

  • Design data models and build cloud data pipelines on Snowflake and AWS

Requirements

  • Previous experience in Data Engineering, Analytics Engineering or Data Platform Engineering

  • Strong data modelling, including conceptual, logical, physical and dimensional modelling

  • Proficiency in SQL

  • Previous technical experience with Snowflake and AWS

  • Experience building and maintaining production data pipelines

  • Good knowledge of data warehousing and modern data architectures

  • Experience with Git, CI/CD and automated testing

  • Understanding of data quality, governance, security and monitoring

Desirable

  • Experience with real-time streaming or event-driven pipelines, such as Kafka or Kinesis

  • Terraform or another Infrastructure-as-Code tool

  • Experience in financial services or another regulated industry

  • Knowledge of Snowflake features such as Snowpipe, Streams, Tasks or Dynamic Tables

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 Lead Data Engineer contract role in Galway focuses on designing data models, building cloud data pipelines (primarily on Snowflake and AWS), and modernizing a large analytics platform while collaborating with both technical and business stakeholders.

  • Hands-on technical expertise·High
  • Data modeling and architecture·High
  • Cloud platform experience (Snowflake, AWS)·High
  • 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 Modeling Projects

    0–7 min

    Select 1-2 strong examples of data modeling work (conceptual, logical, physical, dimensional) to discuss in detail.

  2. Refresh Knowledge of Snowflake and AWS Data Pipelines

    7–14 min

    Revisit your experience with Snowflake features and AWS services, focusing on pipeline design, deployment, and monitoring.

  3. Prepare Examples of CI/CD and Automated Testing

    14–19 min

    Identify specific instances where you implemented CI/CD and automated testing in data engineering projects.

  4. Summarize Data Quality and Governance Practices

    19–24 min

    Outline your approach to data quality, governance, and security, with examples from previous roles.

  5. Draft Targeted Questions for the Interviewer

    24–30 min

    Prepare 2-3 thoughtful questions about the project, team, and technology stack to demonstrate your engagement.

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

  • Data Modeling (Conceptual, Logical, Physical, Dimensional)

    Demonstrate your ability to design robust data models that support analytics and reporting needs; prepare examples of models you've built and the rationale behind your design choices.

  • Building and Maintaining Cloud Data Pipelines

    Showcase your experience with end-to-end pipeline development on Snowflake and AWS, including challenges faced and solutions implemented.

  • Implementing CI/CD and Automated Testing in Data Engineering

    Highlight your approach to ensuring code quality, reliability, and rapid deployment in data engineering projects using Git and CI/CD tools.

  • Data Quality, Governance, Security, and Monitoring

    Explain how you have ensured data integrity, compliance, and operational monitoring in previous roles, especially in regulated or large-scale environments.

  • Modernizing Analytics Platforms

    Prepare to discuss your experience with platform modernization, including migrating legacy systems, adopting new architectures, or introducing new technologies.

What to research

, 4 items

  • Snowflake and AWS Data Engineering

    Review your hands-on experience with Snowflake features (e.g., Snowpipe, Streams, Tasks) and AWS services relevant to data pipelines.

  • Data Modeling Techniques

    Refresh your knowledge and examples of conceptual, logical, physical, and dimensional data modeling.

  • CI/CD and Automated Testing in Data Engineering

    Prepare to discuss your experience with Git, CI/CD pipelines, and automated testing frameworks for data workflows.

  • Data Quality, Governance, and Security

    Be ready to explain your approach to ensuring data quality, governance, and security in production environments.

Questions to ask

, 6 items
  1. What are the main goals for modernizing the analytics platform over the next 12 months?

    Why ask this? Clarifies project scope and expectations for the contract period.

  2. Which Snowflake and AWS features or services are most critical to your current data architecture?

    Why ask this? Helps you understand the technical priorities and where your expertise will be most valuable.

  3. How is success measured for this role and the modernization project?

    Why ask this? Gives insight into performance metrics and deliverables.

  4. What is the team structure and how does this role interact with other stakeholders?

    Why ask this? Clarifies collaboration expectations and reporting lines.

  5. Are there any specific challenges or pain points the team is currently facing with the analytics platform?

    Why ask this? Identifies immediate priorities and areas where you can add value quickly.

  6. What is the process for introducing new tools or technologies into the data platform?

    Why ask this? Assesses openness to innovation and your potential influence on technology choices.

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Apply NowApply before: 15 Nov 2026