Job Description

The Role

Purpose

To design, build, and maintain robust, scalable data infrastructure that ensures secure, real-time access to operational and supply chain data. This role underpins accurate reporting, advanced analytics, and automation--enabling performance optimisation, cost reduction, and smarter decision-making across the logistics value chain.

Duties:

Design, build, and maintain ELT pipelines Data latency (extraction to availability) Error resolution turnaround time Integrate data across systems (WMS, TMS, ERP, IoT) Number of successful system integrations Data completeness and consistency across sources Average time to onboard new data source System uptime and availability Query performance (execution speed) Data quality score (accuracy, completeness, validity) Number of reported data issues Time to deliver datasets for reports/models Internal stakeholder satisfaction rating Compliance with access control policies Number of unauthorised access incidents Audit readiness/ completion rate Manual hours reduced via automation Number of recurring tasks automated Stability of automated workflows Time to issue resolution (from investigation to recommendation) Number of root causes correctly identified Query performance improvements (execution speed, efficiency) SQL-based data validation, transformation, and cleansing coverage Reusable SQL pipelines for recurring logistics workflows (inventory, shipments, routing) SQL-based reconciliation across multiple systems Version-controlled, documented SQL scripts aligned with governance standards Reduction in errors or rework due to SQL inefficiencies

Skills and Experience

Minimum Requirements (Experience & Qualifications)

Bachelor's/Masters in Computer Science or related field



Preferred certifications:


Microsoft Certified: Azure Data Engineer Associate Google Professional Data Engineer AWS Certified Data Analytics Certifications in BI or analytics tools (e.g. Power BI, Tableau, SQL)

3-5 years' experience in data engineering, preferably in logistics, supply chain sectors

Required Knowledge:

Development of ELT/ETL pipelines using tools like Apache Airflow, SSIS, or Azure Data Factory Data integration across logistics systems (ERP, WMS, TMS, IoT) Data modelling, schema design, and SQL optimisation Data warehousing concepts (e.g. star/snowflake schemas) Version control and CI/CD pipelines for data products Supply chain/logistics data structures and flows

Required Skills:

Advanced proficiency in SQL and Python or another scripting language Strong debugging, problem-solving, and performance tuning skills Data validation, cleansing, and transformation techniques Building scalable and reusable data pipelines Communication skills Working knowledge of cloud-based data platforms (e.g. Azure, AWS, GCP)

Other

Required Competencies:

Ability to work under pressure Time management Collaboration Problem solving Attention to detail Analytical thinking Working under pressure in an agile environment


Job Reference: RTT74779