Senior Analyst, Digital Analytics & Automations Solutions

JOB PURPOSE:

Manage the design, development, standardization, and implementation of data analytics, automation solutions, artificial intelligence (AI) and machine learning (ML) to enhance business operations, optimize decision-making, and leverage emerging technologies. Collaborate closely with stakeholders to identify, prioritize, and address key business use cases while ensuring data integration and effective utilization of analytics tools and technologies.

KEY ACCOUNTABILITIES:

Job Specific Accountabilities

Comprehensive analytics framework and solution development.

• Define a comprehensive analytics framework tailored to emerging business needs, focusing on organizing, sharing, and utilizing data effectively.
• Collaborate with business leadership to build a robust business intelligence platform that enables data-driven decision-making.
• Leverage predictive modelling and machine learning capabilities to drive better business outcomes and accurate forecasting.
• Develop advanced analytics models to support data-driven decision-making.
• Oversee the full lifecycle of AI solutions, from data collection and model development to deployment and continuous improvement.
  
  

Develop and Manage Data Pipelines:

• Design, build, and optimize data pipelines for the seamless extraction, transformation, and loading (ETL) of large-scale datasets from various sources into centralized systems.
• Create and maintain optimized data architectures and models that ensure efficient data flow, and retrieval across the organization.
• Ensure the accuracy, consistency, and security of data by implementing data quality checks, validation procedures, and adhering to governance frameworks.
• Ensure Data Security and Compliance
  
  

Business needs analysis.

• Collaborate with business stakeholders to identify, prioritize, and document business use cases that can benefit from analytics, and/or automation.
• Create detailed documentation of analytics and automation requirements, translating them into technical specifications and solution design to guide development efforts.
  
  

Solution design

• Design scalable and sustainable analytics and automation solutions and ensure the alignment with the standards.
  
  

Vendor management

• Identify and select suitable vendors for software development.
• Define clear vendor expectations and deliverables.
• Monitor vendor performance and adherence to project timelines.
• Manage vendor relationships and communications.
• Ensure consistency and maintainability of vendor-delivered solutions.
• Resolve issues and escalations with vendors promptly.
  
  

Technical support and troubleshooting

• Provide technical support for analytical and automation solutions related queries within the organization.
• Troubleshoot and resolve analytical and automation solutions issues to maintain system reliability.
• Collaborate with teams to escalate and resolve complex technical issues, ensuring effective problem resolution.
  
  

Security policy and data protection

• Adhere and implement security policies defined by GD&CS.
• Implement audit recommendations as per internal/external audits reports and vulnerabilities mitigations actions as per vulnerabilities reports generated and shared by ADNOC GD&CS
• Deploy effective incident response plans.
• Ensure data privacy, compliance, and documentation.
  
  

Health, safety, environment (HSE) and sustainability

• Ensure compliance with relevant HSE policies, procedures & controls and applicable legislation and sustainability guidelines in line with international standards, best practices, and corporate code of practices to ensure integrity and safety of assets.
  
  

COMMUNICATIONS & WORKING RELATIONSHIPS:

Internal

• All internal functions and business leadership
• ADNOC HQ
• Shared Services
  
  

External

• Vendors
• Government authorities
• Regulatory bodies
• Industry associations
  
  

Partners and affiliates

QUALIFICATIONS, EXPERIENCE, KNOWLEDGE & SKILLS:

Minimum Qualification

• Bachelor’s degree in computer science, IT engineering or equivalent.
  
  

Minimum Experience & Knowledge & Skills

• 5 years of experience in data engineer, Automation and Analytics, with a focus on developing and managing analytics solutions.
• Proficiency in data manipulation, analysis, and visualization.
• Familiarity with big data technologies, such as Hadoop and Spark, for processing and analyzing large-scale datasets.
• Solid experience to develop & implement AI models and algorithms.
• Deep understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep neural networks, and reinforcement learning.
• Excellent problem solving and analytical skills, with the ability to break down complex problems.
• Strong communication skills.
  
  

behavioural CompetenciEs:

• As per the approved competency dictionary
  
  

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