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 emerging to experienced professionals - to build the next generation of our Talent Cloud platform through scalable data pipelines, storage systems, and analytics infrastructure 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, working with software engineers, data scientists, and product experts in a culture that values innovation, ownership, and continuous learning.

• 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 using platforms (e.g., Kafka, AWS Kinesis) for real-time data processing
• Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence
• Collaborate with data scientists, software engineers, and product teams to deliver reliable data solutions
• Troubleshoot and resolve data-related issues whilst maintaining data quality and integrity
• Write automated tests and participate in code reviews to maintain code quality
• Contribute to best practices, frameworks, and tools for data engineering excellence

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience)
• 0-2 years of experience building data pipelines and systems
• Proficiency in Python and SQL; familiarity with Java
• SQL skills and experience with relational and non-relational databases (e.g., SQL Server, PostgreSQL, MySQL, MongoDB)
• Familiarity with cloud platforms (AWS preferred) and data storage services (e.g., S3, Redshift)
• Familiarity with streaming platforms (e.g., 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), and API development for data consumption
• Knowledge of version control (Git), CI/CD pipelines, and security principles for data systems (encryption, IAM, compliance frameworks)
• Strong analytical and problem-solving skills with intellectual curiosity
• Strong communication and collaboration skills across both technical and non-technical teams