Data Engineer (Python, SQL, Data profiling, Reconciliation and Modeling)

Data Engineer – Data & Application Support

Role Overview

We are looking for an experienced Data Engineer to develop, enhance, and support data pipelines and integration solutions. The role covers the full delivery lifecycle, from requirements analysis and technical design to development, data quality, production support, and ongoing optimisation.

Key Responsibilities

Data Engineering & Development

• Design, develop, test, and maintain scalable data pipelines, data models, and integration solutions.
• Ingest, transform, and curate data from multiple internal and external sources for downstream systems and analytics.
• Translate business, functional, and data requirements into reliable and maintainable technical solutions.
• Partner with business analysts to validate business rules, data mappings, transformation logic, and user requirements.
• Perform data profiling, reconciliation, testing, and root-cause analysis to maintain data accuracy, completeness, and consistency.

Application & Production Support

• Manage application enhancements, defects, production incidents, and change requests through proper assessment, testing, and implementation.
• Provide BAU support for data platforms and pipelines, including monitoring, incident investigation, troubleshooting, and remediation.
• Monitor system and pipeline performance and implement improvements in automation, performance, reliability, and resilience.

Documentation & Governance

• Maintain technical documentation including data flow diagrams, pipeline designs, data models, mappings, interface specifications, and operational runbooks.
• Implement appropriate data governance, security, risk, and technology controls across data solutions.
• Ensure solutions comply with internal data management and technology standards.

Requirements

• Degree in Computer Science, Information Technology, or a related discipline.
• Minimum 5 years of hands-on experience in data engineering and/or application support.
• Strong hands-on proficiency in Python and SQL.
• Experience with data pipelines, data integration, data transformation, data modelling, and data quality.
• Strong troubleshooting and analytical skills, particularly within production environments.
• Good written and verbal communication skills.
• Adaptable, quick to learn, and comfortable working in an Agile environment.