About the Company
Unisys is a global technology company delivering enterprise-level solutions across cloud, infrastructure, and digital services. The organisation operates in a high-end technological environment and focuses on large-scale transformation projects for clients worldwide. It promotes a culture built around innovation, inclusion, and continuous learning, with structured support for employee development and wellbeing.
About the Role
A Data Engineer role is available within a high-impact engineering environment focused on building and maintaining scalable data systems. The position involves designing robust data pipelines, managing data platforms, and supporting analytics-ready datasets used across business functions. The role requires close collaboration with developers, architects, and stakeholders to deliver reliable and efficient data solutions.
Responsibilities
- Design, build, and maintain scalable ETL-ELT data pipelines
- Develop and manage data models, data lakes, and data warehouses
- Ensure data reliability, integrity, and performance across systems
- Implement data governance, security, and compliance best practices through architecture design
- Optimize distributed data processing using frameworks such as Spark
- Work with cloud platforms such as Azure, Databricks, AWS, and GCP to build scalable infrastructure
- Collaborate with developers, architects, and stakeholders to deliver clean and accessible datasets
- Monitor, troubleshoot, and improve existing data workflows
- Stay updated with emerging technologies and best practices in data engineering and application development
Requirements
- At least 5+ years of experience in data engineering or related roles
- Strong proficiency in Python (must have) and good understanding of Scala or Java
- Strong experience with SQL (must have) and NoSQL databases for data modelling and transformation
- Hands-on experience with Spark as a distributed data processing framework
- Familiarity with cloud platforms, especially Azure (preferred over AWS and GCP)
- Experience with data warehouses such as Snowflake, Redshift, or BigQuery, and data lake technologies such as S3, Delta Lake, or Iceberg
- Experience building pipelines using tools such as Airflow, Apache NiFi, or Prefect
- Experience with Databricks is a plus, experience with data build tools is required
- Experience with CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps is an advantage
- Strong problem-solving, communication, and leadership skills with the ability to drive technical decisions
- Ability to work independently and collaboratively in an agile, fast-paced environment