Data Engineer (All Levels)
Build and maintain scalable data pipelines and infrastructure for a talent-cloud platform, enabling analytics and AI-driven features using Python, SQL, cloud services, and streaming tech.
- Compensation
- Not disclosed
- Location
- Dublin, Ireland
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent professional experience)
- Experience building and maintaining large‑scale data pipelines and systems
- Proficiency in Python; familiarity with Java
- Strong SQL skills and experience with relational and non‑relational databases (e.g., SQL Server, PostgreSQL, MySQL, MongoDB)
- Hands‑on experience with cloud platforms (AWS preferred) and services like S3, Redshift, or BigQuery
- Experience with streaming platforms (Kafka, AWS Kinesis) and event‑driven architectures
- Understanding of data modelling, warehousing, and schema design principles
- Familiarity with data transformation tools (e.g., dbt), BI platforms (e.g., Looker, Tableau), and API development for data consumption
- Knowledge of version control (Git), CI/CD pipelines, and security principles for data systems (encryption, IAM, compliance frameworks)
- Experience with user behaviour tracking platforms (e.g., Snowplow, Google Analytics) is a plus
- Strong analytical and problem‑solving skills with intellectual curiosity
- Strong communication and collaboration skills across both technical and non‑technical teams
- For senior‑level candidates: demonstrated experience in mentoring, leading projects, or driving strategic data initiatives
Full description
Job Overview
At iCIMS, we're redefining how people connect with opportunity through intelligent, human‑centred technology. We're growing rapidly and are seeking Data Engineers at multiple levels of experience—from early career to experienced professionals—to build the next generation of our Talent Cloud platform through scalable data pipelines, storage systems, and analytics solutions that power our data‑driven decision‑making and AI capabilities.
You'll design, build, and optimise data infrastructure that supports analytics, business intelligence, and product development. You'll collaborate with software engineers, data scientists, and product experts in a culture that values innovation, ownership, and continuous learning.
This is a hybrid position based in Dublin city centre, our strategic hub for AI development in Ireland.
Responsibilities
- Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources
- Build and optimise data infrastructure to support analytics, reporting, and AI/ML workloads
- Implement event sourcing and streaming architectures (e.g., Kafka, AWS Kinesis) for autonomous agents and reactive systems
- Apply security‑by‑design principles, data governance, and best practices to all data solutions, ensuring compliance with enterprise standards and regulatory requirements
- Collaborate with engineering, product, and business stakeholders to deliver reliable data solutions
- Troubleshoot and resolve data‑related issues whilst ensuring data quality and integrity
- Stay up to date with the latest industry trends and technologies to drive innovation within the team
- Contribute to best practices, frameworks, and tools for data engineering excellence
- For senior‑level candidates: mentor junior engineers and lead technical initiatives
Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent professional experience)
- Experience building and maintaining large‑scale data pipelines and systems
- Proficiency in Python; familiarity with Java
- Strong SQL skills and experience with relational and non‑relational databases (e.g., SQL Server, PostgreSQL, MySQL, MongoDB)
- Hands‑on experience with cloud platforms (AWS preferred) and services like S3, Redshift, or BigQuery
- Experience with streaming platforms (Kafka, AWS Kinesis) and event‑driven architectures
- Understanding of data modelling, warehousing, and schema design principles