Digital & Data Engineer (2 Year FTC) in Tilbury

As part of Bouygues Construction's Public Works division, VSL International participates in the construction of major technical structures and guarantees their structural safety and durability: transport infrastructure (bridges, tunnels), industrial and energy production structures, and commercial buildings.

VSL's Business Is Based On Four Areas Of Expertise:

• Structural systems and technologies
• Civil engineering
• Foundations and soil engineering
• Preservation, structural repairs, renovation and optimisation of structures

VSL has 4,000 employees at 25 locations worldwide (Asia and Oceania, Middle East, Europe, Latin America, Canada).

Position: Digital & Data Engineer to support the rollout of digital systems and deliver robust data solutions across our ground engineering operations. This hybrid role combines digital implementation and data engineering, focused on improving how site data is captured, integrated, and used. You will work closely with site teams, project managers, and digital specialists to ensure accurate, timely, and structured data is available to support operational performance, commercial tracking and data‑driven decision‑making. This position is ideal for an early‑career to mid‑level professional looking to build experience across both digital delivery and data engineering within a major infrastructure environment.

Main Responsibilities

• Digital Rollout: Deploy and configure digital tools and systems across the project (e.g. site reporting and data capture platforms). Drive adoption of digital solutions and workflows across site teams. Provide training, user support and troubleshooting to ensure effective use of systems. Act as the interface between site teams and the digital team to align solutions with operational needs. Monitor system usage and continuously improve digital processes based on user feedback.
• Data Modelling & Transformation: Design, develop and maintain scalable data pipelines using Python and SQL. Integrate external data sources via APIs, including authentication, extraction and automated ingestion. Transform raw data into structured, analytics‑ready datasets aligned to project data models. Monitor and maintain data quality across all stages (raw to processed to reporting). Implement automated workflows, including incremental loads and validation checks. Ensure consistency, integrity and reliability of data across systems. Translate business and operational requirements into scalable data solutions. Produce clear technical documentation covering pipelines, data models and integrations.
• Data Engineering: Design, develop and maintain Power BI dashboards and reports. Create visualisations that clearly communicate trends, patterns and exceptions. Build automated refresh schedules, row‑level security and governance standards. Ensure reports meet accessibility and usability standards for end users.
• Data Governance & Compliance: Ensure compliance with UK data protection and information governance requirements (including GDPR). Proactively identify and resolve data quality issues. Support best practices in data management and standardisation across the project.
• Stakeholder Engagement & Support: Work closely with site teams, engineers and project leadership to understand operational needs. Communicate technical concepts clearly to non‑technical stakeholders. Support adoption of digital tools and data‑driven ways of working. Collaborate with IT and digital teams to ensure alignment across systems and processes.
• Continuous Improvement: Identify opportunities to improve processes, automation and efficiency. Contribute to the ongoing development of digital and data capabilities across the project. Stay up to date with relevant tools, technologies and industry best practices.

Education: Degree in Computer Science, Data Science, Civil Engineering, Geotechnical Engineering or a related discipline preferred.

Experience: Experience in digital system rollout, implementation or user adoption in operational environments. Exposure to data engineering concepts (data pipelines, APIs, data modelling). Experience working with stakeholders across technical and non‑technical teams. Strong problem‑solving skills with attention to detail. Comfortable working with data across multiple systems.

Technical Skills: Proficiency in Python and SQL. Understanding of data engineering principles and data lifecycle management. Experience with APIs and data integration. Familiarity with cloud data platforms (desirable). Ability to translate operational/site requirements into digital and data solutions.