Data Engineering Consultant

About the role

The Data Engineering Consultant designs, builds and supports reliable data pipelines, integrations and services that enable client analytics solutions. Working closely with architects, analysts, platform teams and security specialists, you will translate approved architectures and business requirements into tested technical components that ensure data quality, lineage, security and operational monitoring.

Key responsibilities

• Analyse approved requirements, source systems, target models, data volumes and schedules.
• Design and build batch, streaming or API‑based ingestion and transformation pipelines.
• Implement source‑to‑target mappings, business transformations, reference‑data logic and data‑standardisation rules.
• Embed validation, reconciliation, exception handling and data‑quality controls within workflows.
• Capture technical metadata, lineage, schedules, dependencies and operational information.
• Apply security, privacy, classification, access, encryption and logging requirements.
• Develop automated unit, integration, regression and data‑validation tests and retain execution evidence.
• Optimise performance, scalability, reliability and cost within platform constraints.
• Implement deployment automation, version control, configuration management and controlled release practices.
• Monitor pipeline operation, investigate failures and support defect resolution during implementation and transition.
• Prepare technical specifications, code documentation, support procedures, runbooks and handover records.

Required profile

• Bachelor's degree in computer science, software engineering, data engineering or a related field (or equivalent experience).
• 3–8 years of experience in data engineering, integration, ETL/ELT, software development or cloud data platforms.
• Proven experience building and testing production‑grade pipelines, APIs or data‑processing services.
• Experience with version control, automated deployment, monitoring and operational support.

Required skills

• ETL/ELT design and implementation
• API development and data pipeline engineering
• Version control systems
• Automated deployment and CI/CD practices
• Monitoring and operational support of data workflows