Data Management & Strategy - Oil & Gas - Manager- Consulting

Data Management & Strategy – Oil & Gas – Manager

Location:

Anywhere in Country

Company: EY

EY delivers unparalleled service in big data, business intelligence, and digital analytics built on a blend of custom-developed methods related to customer analytics, data visualization, and optimization. Our methods are not tied to any specific platforms but are driven by business needs and outcome alignment. We are looking for a Data & Analytics Manager to help deliver data-driven insights and solutions to our oil & gas clients.

You will guide clients through the evolving world of analytics, data governance, and modern data platforms, providing strategic leadership and a unique business perspective on how data and analytics can improve operations, increase agility, and drive transformation.

• Lead complex processes and projects, ensuring quality and risk management while navigating organizational dynamics.
• Design and apply comprehensive methods and practices to govern the entire lifecycle of data assets, ensuring their protection and monetization.
• Perform maturity assessments on data management capabilities and advise on tools and roadmaps to implement them.
• Define and execute the analytics and data governance strategy for oil & gas clients, aligning with business objectives and regulatory requirements.
• Develop and implement robust data governance frameworks, including policies, data stewardship models, roles, and accountability across the organization.
• Oversee Master Data Management (MDM), metadata management, and data cataloging practices to ensure data consistency, discoverability, and trust.
• Ensure compliance with data privacy, protection, and regulatory standards (e.g., GDPR, CCPA) in collaboration with Legal, Security, and Risk teams.
• Lead and mentor a multidisciplinary team of analysts, engineers, and data stewards to deliver high-quality outcomes and maintain stakeholder confidence.
• Design scalable, secure, and cost-effective data architectures in collaboration with enterprise architects and IT to support business intelligence and advanced analytics needs.
• Oversee cloud-based data management platforms and technologies such as Databricks, Snowflake, Azure, AWS, and Hadoop for ingestion, storage, and processing.
• Drive the design and implementation of analytical models, data pipelines, and visualizations to solve complex business problems and generate actionable insights.
• Translate business initiatives into prioritized use cases with measurable ROI and manage delivery across multiple domains.
• Develop and champion data literacy programs, training, and change management initiatives to embed a data-driven culture across client organizations.
• Communicate analytical findings through compelling data storytelling, dashboards, and visualizations tailored to business and technical audiences.
• Build and maintain trusted relationships with client stakeholders across operations, IT, engineering, and executive leadership.
• Stay abreast of emerging technologies, oil & gas domain trends.

• A bachelor’s degree required; master’s degree preferred in a quantitative or technical field (e.g., statistics, computer science, engineering, mathematics) with prior consulting experience required.
• At least 6 years of relevant experience in data analytics, data governance, or data strategy, preferably in the oil & gas industry.
• Demonstrated success in deploying analytics solutions across different oil & gas domains (upstream, midstream, downstream).
• Deep knowledge of data governance, including data quality frameworks, stewardship models, compliance, and policy creation.
• Experience in Master Data Management (MDM), metadata, lineage tracking, and data catalog tools (e.g., Collibra, Alation).
• Proficiency with data analytics tools and platforms: SQL, Python, R, Power BI, Tableau, Cognite, Palantir, Dataiku, or similar.
• Expertise in advanced analytics, data science, and machine learning approaches to solve operational or financial challenges.
• Hands‑on experience with big data and cloud platforms such as Databricks, Snowflake, Azure (Data Factory, Azure
  
  ML), AWS, Hadoop.
• Ability to lead large‑scale digital…