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Graduate Data Engineer-UAE National

Job in Abu Dhabi, UAE/Dubai
Listing for: WOODplc
Full Time position
Listed on 2026-06-03
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 120000 - 200000 AED Yearly AED 120000.00 200000.00 YEAR
Job Description & How to Apply Below

Wood is seeking a motivated Emirati graduate to join a fast‑track trainee role focused on applying AI, data science and digital technologies across complex energy and process plant projects.

The successful candidate will support the integration of AI into project delivery, information management and asset lifecycle processes. This will include working with data, documents, engineering systems and digital tools to identify opportunities for automation, improved decision‑making and more efficient delivery.

This role would suit a graduate with a degree in Artificial Intelligence, Data Science, Computer Science, Software Engineering, Computer Engineering, Mathematics, Statistics
, or another relevant discipline with strong data, coding or AI exposure.

Exposure to ADNOC projects
, major energy assets, industrial data environments, digital engineering or complex process plant studies would be beneficial.

Wood will provide strong mentoring, structured development and hands‑on project exposure. The successful candidate will work with experienced digital and information management specialists and will play an integral role in helping Wood apply AI across the full asset lifecycle.

What We Can Offer
  • Meaningful and interesting projects delivered to high‑profile clients across the energy sector
  • Commitment to diversity and inclusion across all levels of the organization
  • Competitive remuneration package with regular market reviews
  • Medical insurance for inpatient and outpatient care
  • Group life and personal accident insurance
  • End of service gratuity in line with UAE labor law
  • Employee Share Plan with company matching
  • Long Service Awards recognizing employee dedication at 5‑year milestones
  • Tailored professional development plans
  • Global collaboration with experts shaping industry standards
  • Energy Transition Academy for knowledge sharing and exposure to emerging energy systems
Key Objectives for This Role:
  • Support Data Pipeline Development
    Assist in building, maintaining, and monitoring data pipelines that collect, process, and store structured and unstructured data from multiple sources.
  • Ensure Data Quality & Reliability
    Perform data validation, cleansing, and basic reconciliation to ensure accuracy, consistency, and reliability of datasets used for reporting and analytics.
  • Work with Databases & Data Platforms
    Support the management of relational and cloud‑based databases, including data loading, querying, and performance optimization under supervision.
  • Collaborate with Cross‑Functional Teams
    Work closely with data analysts, data scientists, IT, and business teams to understand data requirements and translate them into technical solutions.
  • Support Reporting & Analytics Enablement
    Prepare datasets and data models that enable dashboards, reports, and analytical use cases.
  • Learn Modern Data Engineering Tools
    Gain hands‑on experience with ETL/ELT frameworks, cloud data platforms, version control, and automation tools used within the organization.
  • Follow Data Governance & Security Standards
    Adhere to organization policies related to data privacy, security, and compliance while handling sensitive and confidential information.
  • Document Data Processes & Solutions
    Maintain technical documentation for data pipelines, data dictionaries, and operational procedures to ensure knowledge continuity.
  • Identify Improvement Opportunities
    Proactively suggest improvements to data workflows, performance, and process efficiency as technical knowledge grows.
  • Build Technical & Professional Capability
    Continuously develop skills in SQL, data modeling, scripting, and cloud technologies through training, mentoring, and on‑the‑job learning.
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