Enforce data quality standards through validation checks, cross-source consistency controls, adherence to formatting specifications, and systematic verification prior to delivery.
Scale scraping operations for large datasets using efficient batching or parallelization, monitor failures, and maintain stability against minor site structure changes.
At least 3 year of relevant experience in data engineering, web scraping, automation, or software development (required).
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Lead the design and development of chatbot and automation workflows using Microsoft technologies such as MS OpenAI, AI Search, AI Foundry, and Power Platform, while conducting evaluations of large language models from key market providers.
Encourage experimentation and prototyping to drive digital transformation and provide advisory support across a broad range of AI-related technologies.
Implement security measures to safeguard data and AI models, ensuring adherence to established security policies and standards.
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Knowledge of the Cristie BMR solution used in combination with Rubrik.
Knowledge of Veritas NetBackup/Alta Data protection, Veritas Alta View / NetBackup IT Analytics is a plus.
Recording of requirements, analysis, consulting, technical support regarding possible data backup solutions and coordination during implementation.
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Contribute to innovative security and infrastructure projects, both locally and across the region—get hands-on experience in design, benchmarking, installation, and commissioning.
Assist with documentation, audits, reporting, and ensuring compliance with security policies and operational procedures.
Embrace continuous learning by applying your academic knowledge to solve real-world challenges in the data centre environment.
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Client Environment: Data Centre / Network Infrastructure Operations
Job Summary
We are looking for a Data Centre Network Technician / Engineer to support data centre operations with a strong focus on network infrastructure, troubleshooting, configuration, and connectivity support.
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Lead the design and development of chatbot and automation workflows using Microsoft technologies such as MS OpenAI, AI Search, AI Foundry, and Power Platform, while conducting evaluations of large language models from key market providers.
Encourage experimentation and prototyping to drive digital transformation and provide advisory support across a broad range of AI-related technologies.
Implement security measures to safeguard data and AI models, ensuring adherence to established security policies and standards.
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Develop reusable data science workflows, feature engineering logic, model training pipelines and evaluation frameworks to improve scalability and repeatability.
Work with data engineering and technology teams to ensure data pipelines, model inputs and analytical datasets are reliable, well-structured and fit for production use.
Develop and evaluate Generative AI solutions, including prompt-based workflows, retrieval-augmented generation, embedding pipelines, and other LLM-enabled applications.
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We are looking for a Data Science Algorithm Engineer who can do more than train models. You will own the full lifecycle from scoping ambiguous business problems to deploying production-grade solutions that teams actually rely on. This role sits at the intersection of rigorous modeling and pragmatic engineering; you will be expected to build both.
You will work in fast-moving environments where data infrastructure may be incomplete, requirements will shift, and the measure of success is whether a model genuinely improved a decision.
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Analyze compute, storage, job, and cluster resource usage to improve performance and optimize cloud costs.
Develop or integrate automation scripts and operational tools to improve health checks, releases, scaling, and troubleshooting efficiency.
Collaborate with data engineering, data warehouse, BI, platform teams, and cloud vendors to continuously improve platform reliability and operational efficiency.
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Experience working in engineering data management, demonstrated experience in developing and maintaining project databases for EPCI projects, with exposure to data preparation supporting commissioning activities or operational readiness.
Prior experience in FPSO, offshore platforms, or large EPC/EPCI projects is highly preferred.
Prior background in engineering, commissioning, or operations is beneficial.
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Data Analysis: Analyse real-time and historical data to identify trends, anomalies, and potential issues. Develop strategies for process optimisation based on data insights.
Troubleshooting and Maintenance: Diagnose and resolve SCADA system malfunctions and software bugs. Perform routine maintenance, software updates, and system backups.
Cybersecurity: Implement and maintain cybersecurity measures to protect SCADA systems from unauthorised access, cyber threats, and vulnerabilities.
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