Data Engineer

Requirements

Essential

• Minimum 3 years of experience in data engineering, analytics engineering, orbusiness intelligence development
• Strong proficiency in SQL and experience with data transformation frameworks(e.g., dbt, Apache Spark, or equivalent)
• Hands-on experience building dashboards and visualizations with BI tools (e.g.,Power BI, Tableau, Grafana, Superset, or platform-native tooling)
• Experience designing data models for operational or analytical use cases star schemas, entity resolution, or graph-based asset relationships Ability to work with messy, heterogeneous data from multiple sources and produce clean, reliable outputs
• Understanding of data quality practices including validation, deduplication, lineage, and monitoring

Key Responsibilities

• Data Modelling and Transformation
• Design and maintain data models that unify cyber asset information from diverse
• Build and maintain transformation pipelines that clean, normalise, enrich, andrelate ingested data into a coherent asset inventory
• Establish and enforce data quality standards deduplication, completenesschecks, schema validation, and lineage tracking
• Evolve the data model as new data sources are onboarded, ensuring backwardcompatibility and minimal disruption to existing dashboards
• Dashboard and Visualisation Development
• Build dashboards that address agency-specific use cases including asset visibility,

• vulnerability prioritisation, patch tracking, and incident response readiness
• Collaborate with the Business Analyst to develop compelling data narratives
• selecting the right metrics, views, and drill-downs that connect data to agency decision-making
• Iterate on dashboard designs based on agency feedback, balancing clarity with analytical depth
• Maintain and update existing dashboards as underlying data models or agency requirements evolve Platform Data Operations
• Validate successful data ingestion in coordination with the Platform Infrastructure
• Engineer confirming completeness, freshness, and schema conformance
• Monitor data pipeline health, investigate anomalies, and resolve data quality issues
• Optimise query performance and data refresh schedules to ensure dashboards remain responsive and current Document data models, transformation logic, and dashboard specifications for operational continuity