Data Engineer (Mid–Senior)

The successful candidate will play a key role in designing building and maintaining modern data platforms that support advanced analytics machine learning and business intelligence initiatives.

Key Responsibilities:

Data Engineering:

• Design develop and maintain scalable data pipelines and data platforms.
• Build robust ETL/ELT processes to ingest transform and load data from multiple sources.
• Develop and optimise data layers that support analytics and reporting requirements.
• Ensure data quality integrity lineage and performance across data environments.
• Support both batch and real-time data processing solutions.
• Create and maintain technical documentation and solution designs.

• Engage with stakeholders to understand business and operational requirements.
• Analyse source systems and datasets to identify opportunities and recommend solutions.
• Translate business needs into scalable technical data solutions.

• Develop and maintain cloud-native data solutions across Azure AWS or Google Cloud Platform (GCP).
• Monitor and optimise cloud resource utilisation and associated costs.
• Support the development and maintenance of data infrastructure required for modern analytics platforms.

• Conduct peer reviews and contribute to code quality initiatives.
• Follow SDLC processes documentation standards and governance requirements.
• Implement monitoring troubleshooting and performance optimisation practices

• Work closely with Product Owners Data Scientists Analysts and Engineering teams.
• Provide mentorship and knowledge sharing within the team.
• Participate in standby and support rotations where required.
• Contribute positively to team culture and continuous improvement initiatives.

• Bachelors Degree or Diploma in:
  • Computer Science
  • Information Systems
  • Data Engineering
  • Software Engineering

• Minimum 5 years of Data Engineering experience.
• Proven experience designing and implementing enterprise-scale data solutions.
• Strong experience with Python and SQL.
• Experience working within cloud-native environments.
• Demonstrated ability to deliver solutions independently in a fast-paced environment
• Strong Data Engineering fundamentals and modern data architecture principles.
• Experience building and maintaining high-volume data pipelines.
• Experience with cloud platforms:
  • Google Cloud Platform (GCP)
  • Microsoft Azure
  • Amazon Web Services (AWS)

• Understanding of:
  • Data governance
  • Data quality frameworks
  • Data lineage
  • Security and compliance requirements
• Strong troubleshooting optimisation and problem-solving skills.