ETL Data Engineer

About Us

IMGS are Ireland’s leading supplier of spatial solutions for government, utility and telecommunications industries. Our solutions enable our customers to capture, manage and embed spatial data and engineering documentation into their enterprise information systems.

Our team comprises professionals from backgrounds in engineering, computer science, geographical information systems, project management, training and commerce. This is an outstanding career opportunity for the right candidate to join a young dynamic company and really make a difference.



Educated to at least a degree level.



The successful candidate will ideally possess at least 3 years ETL experience and must have good technical writing and presentation skills. Fluency in English is essential.

This a fantastic opportunity to develop your career in a role with high degree of autonomy and flexibility.


In his/her role as a data engineer may be required to:

  • Understand and document customer business requirements and industry practices

  • Research opportunities for potential new uses for customer solutions

  • Design, construct, install, test and maintain data management systems

  • Build high-performance algorithms, prototypes, predictive models and proof of concepts

  • Integrate data management technologies and software engineering tools into existing customer structures

  • Recommend ways to improve customer data reliability, efficiency and quality

  • Support the sales team in the developing business opportunities through the complete sales life cycle including customer presentations, demonstrations, preparing of proposals and tender responses

  • Support marketing initiatives in the company including presenting at company events, stand demonstrations and company webinars  

  • Collaborate with data architects, modelers and IT team members on delivery of projects

  • Provide customer training and ongoing support


Technical Skills

  • ETL and data integration

  • Statistical analysis and modeling

  • Database architectures

  • Hadoop-based technologies (e.g. MapReduce, Hive and Pig)

  • SQL-based technologies (e.g. PostgreSQL and MySQL)

  • NoSQL technologies (e.g. Cassandra and MongoDB)

  • Python, C/C++ Java, Perl

  • MatLab, SAS, R

  • Data warehousing solutions

  • Predictive modeling, NLP and text analysis

  • Machine learning

  • Data mining

  • UNIX, Linux, Solaris and MS Windows

  • Cloud platforms – Azure, AWS and Google