Key Responsibilities

Data Architecture and Engineering Leadership

• Design and implement scalable, secure, and high-performance data architectures across on-premise Oracle environments and AWS cloud platforms.
• Oversee and optimise Oracle Data Warehouse systems, including ETL processes, OLAP cubes, and data transformation pipelines.
• Develop and implement modern AWS-based data pipelines using technologies such as S3, Redshift, Glue, Lambda, EMR, Kinesis, DynamoDB, and Athena.
• Establish best practices for data ingestion, transformation, storage, and retrieval across hybrid environments.

Data Pipeline and Platform Development

• Drive the adoption of modern data engineering technologies including Spark, Kafka, Airflow, and NoSQL solutions.
• Oversee CI/CD processes for data workflows, ensuring efficient, reliable, and automated deployments.
• Manage version control and DevOps practices using tools such as Git, Jenkins, and Terraform.
• Optimise data processing and storage for cost efficiency, speed, and scalability.

Data Governance and Risk Management

• Implement and maintain data governance, access control, and compliance frameworks across hybrid environments.
• Ensure robust disaster recovery and high availability strategies for critical enterprise data systems.
• Maintain data integrity, security, and compliance across all data engineering solutions.

Stakeholder Collaboration

• Partner with data science, analytics, and data visualisation teams to enable advanced analytics and reporting.
• Engage with business and IT stakeholders across all levels of the organisation.
• Ensure alignment between data engineering initiatives and business strategy.

Minimum Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• Minimum 6 years of experience in data engineering.
• At least 2 years’ experience leading hybrid (on-premise and cloud) data engineering teams.
• Strong proficiency in SQL (Oracle, Redshift) and Python for data processing and automation.
• Strong experience with Oracle Data Warehouse and OLAP environments.
• Strong experience in AWS cloud data architecture and services.
• Deep understanding of ETL pipelines, data lakes, data warehouses, and real-time data processing.
• Experience with CI/CD pipelines, Git, Jenkins, and Terraform.
• Strong knowledge of data governance, compliance, and security frameworks.
• Excellent communication and stakeholder engagement skills.

Additional Criteria

• Strategic thinking and ability to define long-term data engineering vision.
• Strong problem-solving and troubleshooting capability in complex data environments.
• Ability to adapt and thrive in fast-paced, evolving technology environments.
• Strong collaboration and communication skills across technical and business teams.
• Commitment to continuous learning and innovation.
• Strong leadership values including integrity, accountability, and collaboration.

If you meet the above requirements and are ready to take on a strategic leadership role in a dynamic data environment, we encourage you to apply.
If you have not heard from us by 20 June, please consider your application unsuccessful.