Data Engineering Lead - Onsite Dublin, Cloud & AI

TopTalent Recruitment Agency

Dublin

On-site

EUR 110,000 - 140,000

Full time

5 hours ago
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Benefits offered by this job

Competitive salary
Leadership opportunity
Global engineering environment
Enterprise-scale platforms

Job summary

Top Talent Recruitment is working with a leading tech outsourcing company to recruit a Data Engineering Lead to join their team in Dublin, Ireland. This full-time role will lead the design, development and deployment of scalable data systems for analytics and AI initiatives.

You will drive large-scale data pipelines, collaborate with data scientists and engineers, mentor a squad of data engineers, and promote best practices in cloud-based platforms and ETL/ELT workflows.

Qualifications

  • 8+ years in Data Engineering or Big Data roles.
  • Strong coding in Python/Scala/Java.
  • Hands-on with Spark, Databricks, and Hadoop ecosystem.
  • Experience building scalable data pipelines.
  • Experience leading technical initiatives.

Responsibilities

  • Lead design and implementation of scalable data engineering solutions.
  • Build and optimise large-scale data pipelines for analytics and ML.
  • Define data architecture for scalability and reliability.
  • Mentor data engineers and promote agile practices.
  • Collaborate with data scientists, product managers and engineers.
  • Ensure data quality and platform performance.

Skills

Python
Scala
Java
Spark
Databricks
Hadoop
SQL
NoSQL
Distributed systems
Leadership

Education

Degree in Computer Science or related field

Tools

AWS
Azure

Job description

Top Talent Recruitment is working with a leading tech outsourcing company to recruit a Data Engineering Lead to join their team in Dublin, Ireland. This full-time role will lead the design, development and deployment of scalable data systems for analytics and AI initiatives.

You will drive large-scale data pipelines, collaborate with data scientists and engineers, mentor a squad of data engineers, and promote best practices in cloud-based platforms and ETL/ELT workflows.

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