Data Engineer (Data Platforms)

Our client is seeking a hands‑on Data Engineer to support the operations, maintenance and enhancement of a central data platform. You will work closely with technical teams, source system owners, vendors and business users to build reliable data pipelines and deliver quality datasets for reporting and analytics.

• Develop and maintain ETL/ELT pipelines and file-based interfaces for data ingestion.
• Build SQL and Python solutions for data cleansing, transformation, standardisation and reconciliation.
• Maintain data models, tables, datasets and processing logic to support new requirements.
• Implement data quality, validation and reconciliation checks, investigate anomalies and resolve root causes.
• Monitor and troubleshoot data pipelines, perform reruns and improve pipeline reliability and performance.
• Support system enhancements, testing, UAT, defect resolution and production issues.
• Develop governed datasets, queries and data sources for downstream reporting and analytics.
• Translate business requirements into data mappings and technical solutions, while maintaining clear documentation.
• Support data governance, audit, access review and compliance activities.

• 3-4 years of relevant Data Engineering experience, with strong SQL and working proficiency in Python for data processing, automation and pipeline development.
• Hands‑on experience in ETL/data pipeline development, including data ingestion, transformation, validation and production support.
• Strong understanding of data modelling, data warehousing and relational/file-based data.
• Experience handling complex, inconsistent or legacy data, including data reconciliation, troubleshooting and root‑cause analysis.
• AWS experience preferred, particularly S3, Athena, IAM, CSV/Parquet and partitioned datasets; experience with other cloud data platforms will also be considered.
• Experience with Spark, Databricks or similar technologies is an advantage.
• Experience with Tableau or other BI tools is a plus.