Role Overview
We are looking for experienced Data Engineers to support enterprise data platform. The successful candidate will be responsible for designing, developing, and maintaining scalable data solutions that support data integration, analytics, reporting, and business intelligence needs across the organisation.
This role requires strong hands-on experience in data pipeline development, data transformation, cloud-based data platforms, and modern analytics environments such as Databricks.
Key Responsibilities
Data Engineering & Integration
- Design, develop, and maintain scalable ETL / ELT data pipelines
- Build and optimise data ingestion and transformation workflows from various internal and external data sources
- Develop and maintain batch and real-time data processing solutions
- Integrate enterprise systems and APIs into centralised data platforms
- Ensure data quality, consistency, and reliability across data pipelines
- Data Modelling & Architecture
- Design and maintain conceptual, logical, and physical data models
- Develop and optimise data warehouses, data lakes, and analytical data marts
- Support enterprise data architecture and governance initiatives
- Implement data transformation and modelling best practices for reporting and analytics use cases
Cloud & Analytics Platforms
- Work with cloud-based data platforms such as AWS, Azure, or GCP
- Develop and maintain solutions using platforms such as Databricks and related analytics tools
- Support data analytics and business intelligence initiatives through efficient data preparation and delivery
- Optimise platform performance, scalability, and cost efficiency
Collaboration & Support
- Collaborate with business users, analysts, architects, and cross-functional technical teams
- Support troubleshooting, issue resolution, and production support activities
- Prepare technical documentation and maintain development standards
- Participate in Agile project delivery and continuous improvement initiatives
Requirements
- Degree in Computer Science, Information Technology, Data Engineering, or related disciplines
- Experience in Data Engineering, ETL / ELT development, or data platform implementation
- Strong experience in SQL and data transformation techniques
- Experience with cloud-based data platforms such as AWS, Azure, or GCP
- Hands-on experience with Databricks or similar analytics platforms
- Familiarity with data warehousing, data lakes, and big data concepts
- Experience with scripting/programming languages such as Python, Scala, or Java
- Understanding of data governance, security, and data quality practices
- Strong analytical, troubleshooting, and problem-solving skills
- Good communication and stakeholder management skills
Preferred Skills
- Experience in enterprise analytics or large-scale data platform environments
- Knowledge of orchestration and workflow tools such as Airflow or Azure Data Factory
- Exposure to DevOps, CI/CD, and infrastructure automation practices
- Experience supporting government or regulated industry environments is an advantage