Data Engineer - Build the Data Backbone 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 gas capital of the world, we bring deep industry expertise together with cutting-edge digital thinking to transform how energy companies work, connect, and grow.
If youre driven by impact, speed, and purpose not titles or bureaucracy youll fit right in.
About ADAPT
ADAPT is our flagship digital platform a real-time digital mesh connecting the energy sectors Maintenance, Repair & Operations (MRO) ecosystem.
It replaces slow, fragmented processes with real-time intelligence and automation, connecting operators, contractors, and suppliers through live data, adaptive analytics, and secure, human-in-the-loop governance.
Built on Microsoft cloud and AI, ADAPT delivers visibility, intelligence, and agility at industrial scale redefining how energy companies collaborate and compete.
About the Role
We are hiring a Data Engineer to design and build secure, scalable data infrastructure for the energy sector. This 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 help create the real-time data foundation that powers ADAPT, providing instant visibility and insights that drive smarter, faster, and safer decisions in mission-critical environments.
The ideal candidate will have at least five years professional experience and demonstrate excellence in building well-documented, secure, and reliable data solutions that underpin digital transformation at scale.
Key Responsibilities
Data Pipeline Development & Optimisation
- Design and implement highly optimised pipelines for processing large-scale supply-chain data supplier performance, inventory, procurement transactions, and real-time equipment status.
- Develop maintainable ETL/ELT processes supporting both planned and emergency operations, with emphasis on code reusability and long-term stability for 24/7 uptime.
- Optimise performance to ensure sub-second response for live dashboards and supplier availability.
- Build automated data-quality frameworks to validate supplier qualifications, inventory accuracy, and compliance data essential to safety and reliability.
- Support real-time analytics through streaming data pipelines powering live operational intelligence.
Security & Compliance
- Implement strong data-security controls encryption, access management, and masking.
- Design and enforce data-governance policies aligned with international standards (GDPR, HIPAA, etc.).
- Conduct regular security audits and vulnerability assessments of data systems.
- Apply row- and column-level security to protect sensitive data where required.
Azure Cloud Infrastructure
- Architect and maintain data solutions using Azure Data Factory, Databricks, Synapse Analytics, and Data Lake Storage.
- Integrate Azure Key Vault, Active Directory, and managed identities for secure operations.
- Optimise Azure resources for cost efficiency and performance.
- Design and implement backup and disaster-recovery strategies.
- Leverage Azure Monitor and Application Insights for proactive monitoring and alerting.
Maintainability & Documentation
- Create comprehensive technical documentation for pipelines, architectures, and processes.
- Maintain detailed runbooks and operational procedures.
- Implement version control and CI/CD pipelines for data workflows.
- Document data lineage, transformation logic, and metadata repositories.
Communication & Collaboration
- Communicate technical concepts clearly to both technical and business stakeholders.
- Collaborate with developers, analysts, and business teams to translate requirements into data solutions.
- Provide regular status updates and progress reports to management.
System Maintenance & Optimisation
- Monitor system health proactively and implement preventive maintenance.
- Design with maintainability at the core for fast troubleshooting and iteration.
- Implement automated testing for pipelines.
- Define and uphold SLAs for data availability and quality.
- Optimise storage and retention for cost-effectiveness.
Requirements
Education & Experience
- Bachelors degree in Computer Science, Engineering, or Information Systems.
- Minimum 5 years professional experience in data engineering or related fields.
- Proven success designing and implementing enterprise-scale data solutions.
Technical Skills
- Hands-on expertise with Azure data services Data Factory, Databricks, Synapse Analytics, Data Lake.
- Proficiency in Python, SQL, Scala, or C#.
- Experience implementing data-security and access-control mechanisms.
- Strong knowledge of database-performance optimisation.
- Proficiency in data-quality and governance frameworks.
- Understanding of batch and real-time processing architectures.
Core Competencies
- Documentation excellence: produces clear, thorough, and maintainable documentation.
- Communication: clear, confident, and adaptable to diverse audiences.
- Security mindset: embeds data protection into every design decision.
- Optimisation focus: constantly seeks performance and cost improvements.
- Maintainability approach: builds systems designed for the long term.
- Willingness to travel for client implementations and support.
Why Join Us
At digital.enterprises, youll help build the data engine that transforms how energy ecosystems operate.
Your work will empower people across plants, control rooms, and offices to make decisions in real time supported by data that is secure, trustworthy, and always available.
This is your opportunity to contribute to Industry 5.0 in action technology amplifying human capability to deliver safer, cleaner, and more reliable energy for everyone.