Data Engineer

BUILD THE REAL-TIME INTELLIGENCE OF ADAPT

About digital.enterprises

digital.enterprises is shaping the future of the energy sector. We help companies run smarter integrating people, data, and technology to create intelligent, adaptive, and human-centred operations. Based in Doha, the LNG and GTL capital of the world, we fuse deep industry expertise with cutting-edge digital thinking to transform how energy companies work, connect, and grow. If you are driven by impact, speed, and purpose not titles or bureaucracy you will fit right in.

About ADAPT

ADAPT is our flagship platform a real-time digital mesh connecting the energy sector's Maintenance, Repair & Operations (MRO) ecosystem. Instead of long procurement cycles, ADAPT matches buyer demand with supplier capability instantly, using live data and AI to surface qualified options with governance, auditability, and human-in-the-loop controls.

About the Role

We are hiring a 
Data Engineer
 to design and build the secure, scalable data infrastructure powering ADAPT. The role focuses on developing robust, high-performance data solutions that enable seamless connectivity across the supply chain, from urgent maintenance events to complex planned turnarounds.

You will create and maintain the real-time data backbone that drives ADAPT, ensuring visibility, accuracy, and trust in every data flow. The ideal candidate will have at least five years of professional experience and demonstrate excellence in building secure, well-documented, and maintainable data solutions that support mission-critical energy operations, real-time decision-making, and performance optimisation.

Key Responsibilities

Data Pipeline Development and Optimisation

• Design and implement highly optimised data pipelines to process large-scale operational and supply chain data including supplier performance, inventory levels, procurement transactions, and equipment status across oil and gas operations.
• Develop maintainable ETL and ELT processes supporting both predictive, planned and emergency requirements, with emphasis on code reusability and long-term reliability for 24/7 operations.
• Implement performance optimisation strategies ensuring sub-second response times for live dashboards, supplier availability, and critical performance monitoring.
• Build automated data-quality frameworks to validate supplier qualifications, inventory accuracy, and procurement compliance data essential for operational safety and standards.
• Support real-time analytics by designing streaming data pipelines enabling live visibility, automated capture, and dynamic intelligence.

Security and Compliance

• Implement robust data-security measures including encryption, access control, and data masking.
• Design and enforce data-governance policies and security best practices.
• Ensure compliance with global data protection regulations such as GDPR and HIPAA.
• Conduct security audits and vulnerability assessments.
• Implement row-level and column-level security where appropriate.

Azure Cloud Infrastructure

• Architect and maintain cloud-based data solutions using Azure services such as Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake Storage.
• Implement Azure-native security features including Azure Key Vault, Azure Active Directory integration, and managed identities.
• Optimise Azure resource utilisation for cost-effectiveness and performance.
• Design and implement disaster recovery and backup strategies.
• Use Azure Monitor and Application Insights for system monitoring and alerting.

Maintainability and Documentation

• Produce comprehensive technical documentation covering all pipelines, architectures, and processes.
• Maintain detailed runbooks and operational procedures for system support.
• Implement version-control strategies and CI/CD pipelines for data-engineering workflows.
• Document data lineage, business logic, and transformation rules.
• Create and maintain data dictionaries and metadata repositories.

Communication and Collaboration

• Communicate technical concepts clearly to both technical and non-technical stakeholders.
• Collaborate with developers, analysts, and business stakeholders to understand and translate requirements into actionable data solutions.
• Provide regular progress updates to management and project leads.

System Maintenance and Optimisation

• Proactively monitor system health and implement preventive maintenance strategies.
• Design solutions with maintainability as a core principle to ensure easy troubleshooting and continuous improvement.
• Implement automated testing frameworks for pipelines and data models.
• Define and uphold service-level agreements (SLAs) for data availability and quality.
• Optimise storage costs through intelligent archiving and data-retention policies.

Required Qualifications

Education and Experience

• Bachelor's degree in Computer Science, Engineering, or Information Systems.
• Minimum of five years of professional experience in data engineering or a related field.
• Demonstrated success designing and implementing enterprise-scale data solutions.

Technical Skills

• Hands-on experience with Azure data services including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake.
• Strong proficiency in programming languages such as Python, SQL, Scala, or C#.
• Experience implementing data-security measures including encryption, tokenisation, and access control mechanisms.
• Expertise in performance-optimisation techniques for database queries and workloads.
• Proven capability in developing and maintaining data-quality and data-governance frameworks.
• Knowledge of both batch and real-time data-processing architectures.

Core Competencies

• Documentation excellence: the ability to create clear, comprehensive, and maintainable technical documentation.
• Strong communication skills with proven experience presenting to technical and non-technical audiences.
• A security-first mindset with a strong understanding of data protection and compliance requirements.
• A continuous-improvement and optimisation focus.
• A maintainability approach ensuring systems are robust, well-structured, and future-ready.
• Willingness to travel as required for client implementations and operational support.

Why Join Us

At digital.enterprises, AI is a partner to people, not a replacement. This is Industry 5.0 in practice: technology amplifying human capability so energy operations become safer, more reliable, and more efficient delivering secure, affordable, cleaner energy at scale. You will join a mission-driven team led by credible industry leadership with the freedom to build technology that genuinely changes how an industry works.