Planning Data & Business Intelligence Analyst

About the Role

We are seeking a highly analytical

Planning Data & Business Intelligence Analyst

to support production planning, hydrocarbon accounting, operational performance monitoring, and digital transformation initiatives within a complex industrial environment. The successful candidate will leverage advanced analytics, business intelligence, data engineering, and AI technologies to enhance decision-making, optimize reporting processes, and drive operational excellence.

Qualifications & Experience

• Bachelor's degree in Engineering, Data Science, Computer Science, Information Systems, or a related discipline.

• Minimum 10 years of relevant professional experience.

• At least 5 years of experience in the Oil & Gas, Energy, Industrial Operations, Manufacturing, or Data Analytics sectors.

• Basic understanding of production planning, performance management, and hydrocarbon accounting processes is desirable.

• Familiarity with digital technologies, industrial data systems, and business intelligence platforms.

• Strong analytical, problem-solving, and critical thinking skills.

• Effective communication and presentation abilities.

• Interest in and willingness to work with Artificial Intelligence, Machine Learning, and advanced analytics technologies.

Key Competencies

• Business Intelligence and analytics platforms such as Power BI, Tableau, Qlik, or equivalent tools.

• Data engineering, SQL development, ETL processes, and data integration.

• AI/ML technologies including Python, TensorFlow, PyTorch, and related frameworks.

• Data visualization, dashboard development, and executive reporting.

• Advanced Microsoft Excel skills, including data modelling, trend analysis, and reporting automation.

• Familiarity with production data management systems and operational performance monitoring.

• Proficiency with presentation and process visualization tools such as PowerPoint and Visio.

• Experience in digital transformation, reporting automation, and data-driven decision support.

Key Responsibilities

• Design, develop, and maintain Business Intelligence dashboards supporting production planning, operational performance, and business reporting.

• Streamline and automate reporting workflows using Power BI, Tableau, Qlik, or equivalent analytics platforms.

• Create interactive visualizations and management reports to support decision-making at operational and leadership levels.

• Integrate and consolidate data from multiple operational and business systems.

• Ensure data quality, consistency, reliability, and governance across various data sources.

• Develop, maintain, and optimize ETL processes, data pipelines, and analytical datasets.

• Build and support AI/ML models for forecasting, anomaly detection, performance optimization, and decision support.

• Contribute to predictive analytics initiatives focused on reliability, operational efficiency, and loss prevention.

• Support integration of advanced analytics solutions with production, planning, and business systems.

• Perform scenario modelling and "what-if" analysis to support operational and business optimization.

• Automate manual reporting and planning activities using AI, RPA, and advanced digital technologies.

• Maintain robust data governance, security, compliance, and auditability standards for analytical outputs.

• Deliver training, user support, and knowledge-sharing sessions to business stakeholders.

• Collaborate with Operations, Engineering, Digital, IT, and Business teams to identify and implement data-driven improvement opportunities.

Additional Requirements

• Candidates must demonstrate strong analytical capabilities, data management expertise, and the ability to work effectively across multidisciplinary teams.

• Experience working with operational, industrial, or energy-sector data environments is highly desirable.

• Ability to support both corporate and operational site activities when required.

• Successful candidates will undergo technical and competency-based assessments as part of the selection process.