We're hiring an experienced Data Engineer as part of a large digital transformation project in the public sector. In this role, you’ll configure CRM and iPaaS environments, execute ETL processes for migrating critical data elements, and collaborate with technical and QA teams to ensure seamless integration and validation. If you’re passionate about building robust data pipelines and delivering secure, scalable solutions, we’d love to hear from you!
This is a hybrid role with an expectation of 3 days per week on site in Dublin, Ireland.
Roles and Responsibilities:
- Configures a CRM sandbox test environment – resulting in CRM test environment setup guide.
- Executes ETL for migrating CDEs to potential market-leading target CRM platforms, aligned with the architect’s plan – resulting in ETL scripts/configurations, migration execution report (data volume, performance, issues, accuracy), and validation results.
- Works with both the Technical team and QA lead to implement and test migration resulting in validation reports and collaboration notes.
- Configures iPaaS PoC and test environment, prioritising core CDEs – resulting in iPaaS configuration guide, test environment guide, PoC workflows, PoC test results report, and operational guide.
- Works with EI Technical team (developers, data, security, QA) to implement and test iPaaS – resulting in collaboration notes in PoC test results and operational guide.
Requirements
- 4 + years of extensive professional experience in a data engineering role. Ideally, the proposed candidate should have experience in performing this role in medium to large organisations.
- A bachelor’s degree in computer science, Information Systems, Engineering, or a related field
- Demonstrable experience with Data Architecture especially data pipelines and data warehousing, ETL processes design and implementation, Cloud platforms especially SaaS CRM and data warehousing
Skillsets
- Programming skills
- Data warehousing
- Data modelling
- Data ingestion tooling
- Machine learning workflows
- Real-time/near-time data processing
- Problem Solving
