Data Engineer
Your role
Our Oil & Energy Downstream Client is looking for Data Engineer who will support their digital and data ambitions by ensuring reliable, secure, and highquality data flows across the LNG application and integration landscape. The role focuses on designing, maintaining, and supporting data interfaces, understanding data schemas, mapping data lineage, and ensuring adherence to the Client's data and integration standards. You will enable business value by ensuring trusted data is available for trading, operations, optimization, and analytics use cases.
Responsibilities
Data Integration & Interface Management
- Design,build, and maintain data interfaces between the Client's LNG applications, enterprise platforms, and external partners (e.g., trading systems, scheduling systems, finance applications).
- Support day-to-day operations of data flows, ensuring stability, timely processing, and incident resolution aligned with the Client support processes.
Data Modeling, Schemas & Architecture Alignment
- Understand application and enterprise data models, schemas, and metadata structures, ensuring alignment with the Client's Data Architecture and IT standards.
- Partner with Architects and Data Managers to influence schema design, maintain documentation, and ensure compatibility through system changes and upgrades.
- Contribute to data modelling that supports the Client's LNG's operational, commercial, and analytical requirements.
Data Lineage, Quality & Controls
- Define and maintain end-to-end data lineage across systems, ensuring traceability to source applications and downstream consumers.
- Work with Data Management, Risk Management, and Governance teams to ensure compliance with the Client's data standards, control frameworks, and privacy/security requirements.
- Implement automated data validation, data quality rules, and exception handling aligned with the Client's standards.
Collaboration & Stakeholder Engagement
- Engage with Product Owners, Business Analysts, Solution Architects, and external vendors to translate business needs into technical data integration solutions.
- Support the Client LNG software delivery process by contributing to backlog refinement, solution design, and release planning.
- Provide subject-matter expertise on data flows, interface dependencies, and data usage across the Client LNG processes.
Operational Excellence & Continuous Improvement
- Drive improvements in reliability, observability, and performance of data pipelines using the Client's monitoring and tooling standards.
- Support the move toward more automated, self-service, and reusable data integration capabilities.
- Identify opportunities for simplification and modernization within the data and integration landscape.
You are what we are looking for if you:
- Have 3-5 years of experience in data engineering, data integration or data architect within large-scale, complex environments.
- Have strong technical knowledge in:
- - Azure Data Factory, Logic App, event streaming (e.g., Kafka, data bricks)
- - SQL, relational and NoSQL database structures
- - Data modeling, metadata management, and data lineage tools
- - Python, Scala, or other scripting languages for pipeline design
- Have experience with cloud data platforms (Azure preferred) and modern engineering tooling.
- Have strong understanding of data quality, controls, governance, and metadata standards.
- Have proven ability to troubleshoot production issues and deliver stable, high-quality solutions.
- Have experience supporting applications in energy, commodities trading, or asset operations is advantageous.
- Have demonstrated ability to work in cross-functional teams and communicate with both technical and business stakeholders.
AI Engineer
Your role
Our major Oil & Energy Downstream Client is looking for AI Engineer who will play a key role in the Client's acceleration of Generative AI and agentic automation across the Client Energy LNG and the broader enterprise. The role focuses on designing, developing, and operationalizing agentic AI systems that automate workflows, integrate with enterprise applications, and deliver usable, intuitive front-end interfaces for end users.
You will work closely with product teams, digital delivery, architecture, and data engineering to ensure solutions are secure, compliant, scalable, and aligned with the Client AI and IRM standards.
Agentic AI Development & Automation
- Design, build, and operationalize agentic AI solutions capable of performing multi-step workflows, interacting with enterprise systems, and automating business processes.
- Develop AI agents that can integrate with APIs, enterprise data sources, task schedulers, and workflow engines.
- Ensure agent behavior aligns with the Client's Responsible AI, safety, and control requirements.
Application & Workflow Integration
- Integrate AI systems with the Client Energy applications (e.g., trading, operations, scheduling, finance, document management).
- Build robust connectors to external and internal systems using approved integration patterns (REST APIs, event streaming, messaging, etc.).
- Collaborate with integration teams to ensure secure and reliable connections across the enterprise landscape.
Front-End / User Interface Development
- Design and deliver simple, intuitive, userfriendly UIs (web-based or embedded) that allow end users to interact with AI capabilities
- Build front-end components for:
- -triggering workflows
- - monitoring agent activity
- - visualizing results
- - interacting with conversational or task-based AI assistants
- Ensure UI designs follow the Client UX standards, accessibility guidelines, and security controls.
AI Model Engineering & Governance
- Build and optimize prompts, orchestrators, custom tools, and agent frameworks to support enterprise use cases.
- Work with data teams to ensure AI solutions use high-quality, secure, and compliant datasets.
- Partner with the Client's Responsible AI and Risk Management teams to ensure full compliance with the Client's AI governance frameworks.
Solution Delivery & Support
- Participate in end-to-end delivery: requirements, design, development, testing, deployment, and hypercare.
- Work within Agile teams, collaborating with Product Owners, BAs, Engineers, and Architects.
- Document solutions, operational runbooks, and support guidelines for long-term sustainability.
Innovation & Continuous Improvement
- Evaluate new LLMs, agentic frameworks, and automation tools for potential adoption in the Client.
- Identify opportunities to streamline workflows, reduce manual effort, and enhance business productivity.
- Contribute to the Client's AI Community of Practice and knowledge-sharing forums.
You are what we are looking for if you:
- Have Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence or a related technical field
- Have 35 years of experience in AI engineering, ML engineering, software engineering, or similar technical roles in an enterprise setting.
- Have demonstrated experience delivering agentic AI or workflow automation using one or more of: GenAI prior experience to building AI agent
- - LangChain, AutoGen, Semantic Kernel, or other orchestration frameworks - preferred
- - LLM-based task automation or multi-agent systems - preferred
- Have strong hands-on skills in:
- - Python, JavaScript/TypeScript (preferred), or similar languages
- - Building APIs and backend services
- - Front-end frameworks such as React, Vue, Angular, or Next.js two headcount one have
- Have technical familiarity with:
- - Large Language Models (LLMs) and prompt engineering
- - Workflow orchestration tools (Airflow, Temporal, Azure Logic Apps, etc.)
- - Vector databases, embeddings, and retrieval pipelines
- - Azure cloud services, particularly Azure OpenAI preferred
- Have experience integrating solutions with enterprise systems via approved patterns (APIs, OAuth, event streaming).
- Have strong understanding of data governance, identity & access control, cybersecurity, and AI risk mitigation in a corporate environment.
