Data Management Lead

INEOS•Houston, TX

About The Position

We are seeking a strategic and forward-thinking Data Management Lead to play a pivotal role in shaping and advancing our data capabilities. This is a hands-on leadership role that combines technical credibility with strong managerial, governance, and delivery capability. The position is accountable for defining the operating model for data management, establishing data governance and quality standards, partnering with IT on secure and scalable platform access, and leading planned data engineering, analytics, and AI resources as the team grows. This role will ensure that trusted, well-governed data products are available to support upstream asset management, operations, production surveillance, planning, financial analysis, and executive reporting. The ideal candidate will bring 10+ years of experience in data architecture, data engineering, or a related role, with a focus on the upstream oil and gas sector.

Requirements

Bachelor of Science degree in Data Science, Computer Science, Engineering Information Systems or related
Minimum of 10 years’ experience in data management, data architecture, data engineering, analytics or a related role, with a focus on the upstream oil and gas sector.
Proven experience with Snowflake, Microsoft Azure, and Power BI.
Demonstrated experience establishing, leading, or materially improving data management, data engineering, or analytics function.
Prior team leadership or direct management experience, including coaching, prioritization, workload management, and performance feedback.
Strong data governance experience, including data ownership, stewardship, business definitions, data quality, access controls, and change management.
Exceptional problem-solving abilities and a strategic mindset.
Strong communication skills, with the ability to articulate technical concepts to diverse audiences.

Responsibilities

Develop and execute a comprehensive data management practice, including the operating model, governance framework, delivery roadmap, standards, controls, and resourcing plan.
Define clear roles, responsibilities, decision rights, and ways of working for data management across the business, IT, and future data team members.
Foster a collaborative, business-focused team culture that values transparency, data quality, continuous improvement, and disciplined delivery.
Develop practical standards, reusable delivery patterns, and documentation to enable consistent execution across the team.
Drive innovation by staying current with industry trends and integrating new technologies and methodologies into the data strategy.
Design and implement scalable, secure, and maintainable data architectures using Snowflake, Microsoft Azure, Power BI, and related tools
Develop and manage data models, schemas, pipelines, integrations, curated datasets, and semantic layers that support business intelligence, analytics, and future AI use cases.
Ensure data integrity, security, and compliance with industry regulations and company policies.
Oversee the deployment and optimization of Microsoft Azure cloud services for data storage, processing, and management.
Utilize Power BI to create and maintain interactive dashboards and reports that provide actionable insights to stakeholders.
Collaborate with IT and other departments to ensure seamless integration and performance of data tools and platforms.
Work with IT and cybersecurity resources to ensure data access and integrations are secure, supportable, and consistent with company standards
Establish and maintain practical data governance processes covering data ownership, stewardship, business definitions, data quality, access controls, change control, and issue escalation.
Implement data quality frameworks, monitoring practices, and remediation workflows to improve accuracy, completeness, timeliness, and reliability of critical dataset.
Address and resolve data-related issues and provide ongoing support for data management best practices.
Work closely with business leaders, internal users, analysts, and other stakeholders to understand data needs and translate them into technical solutions with a governed delivery roadmap.
Communicate complex data concepts and architectural designs, trade-offs, risks, and delivery progress effectively to both technical and non-technical audiences.
Recruit, onboard, mentor, and lead data engineering, analytics engineering, and AI resources as the data management team grows.
Providing day-to-day prioritization, coaching, workload management, and performance feedback for team members and supporting contractors or vendors.
Manage relationships with external vendors and partners as needed to support data initiatives.
Lead data and analytics projects from conception through execution, ensuring timely delivery and alignment with business objectives, clear scope, practical timelines, and sustainable support arrangements.
Manage budgets, resources, priorities and vendor support effectively to achieve project goals and maintain business confidence in the data management practice.