Summit Global Health

• The Senior Data Engineer designs, builds and maintains the data ingestion and transformation pipelines that populate Inchcape’s central data platforms. • This role ingests raw data from diverse systems, curates the bronze and silver layers of the medallion architecture, ensures data quality and performance, and delivers reliable, reusable datasets for modelling, analysis, reporting and BI. • Develop and maintain ETL/ELT pipelines to ingest data from ERP, CRM, operational, financial, and third‑party sources into the Microsoft Fabric Platform - Lakehouse (OneLake) using Delta Lake/Parquet. • Implement data quality standards and controls, incremental loading, CDC and error handling to ensure reliability and correctness. • Create bronze tables, curated Silver and gold tables by transforming, cleansing and conforming raw data, document lineage and transformations. • Optimise performance through partitioning, clustering and tuning of MS Fabric, SQL and Spark workloads, monitor pipeline health and costs. • Collaborate with Data Architects, Modellers and Data BAs to design schemas, naming conventions and integration patterns to ensure business self-service enablement through Gold data. • Build reusable components, templates and automation scripts using Fabric Dataflows Gen2, Spark notebooks or equivalent tools. • Maintain metadata and sensitivity labels via Purview, ensure proper access controls and compliance. • Research and evaluate new features and patterns in Microsoft Fabric and make recommendations for adoption, enabling an AI-driven data strategy. • Ensure NFR requirements like resilience, availability and security standards are applied as per agreed NFR metrics.

• Collect and interpret global port tariff data from ports, vendors, and service providers • Analyse and model tariff structures to accurately translate complex charging rules into calculation logic • Build, validate, and maintain tariff calculation logic within the Port Tariff Calculator, ensuring alignment with real world port charging practices • Perform structured data quality checks to ensure accuracy, consistency, auditability, and version control • Maintain clear documentation of data sources, assumptions, and calculation methodologies • Manage high volume tariff workloads across multiple global ports while maintaining quality and pace • Collaborate with internal teams to clarify requirements and ensure tariff data meets operational, digital, and compliance standards • Identify recurring issues and opportunities for standardisation and continuous improvement • Ensure adherence to data integrity, security, and compliance policies at all times