Data Management Lead (Oil and Gas Exp. Needed)

Ledgent Technology; Houston (TX); On-site; USD 175,000 - 180,000; Full time

Benefits offered by this job

Bonus

401k Match

Job summary

Ledgent Technology is seeking an experienced Data Management Lead for an onsite role in Houston, TX. The ideal candidate will drive enterprise‑scale data governance, architecture, and analytics programs within Oil & Gas, bridging technical and business stakeholders.

The role requires 10+ years in data management with cloud platforms (Snowflake/Azure) and strong leadership to mentor teams and manage vendor relationships.

Qualifications

• Bachelor's degree in a related field and 10+ years in data management, architecture, analytics, or data engineering.
• Oil and Gas industry experience is preferred.
• Strong governance, metadata management, data quality, and access controls.

Responsibilities

• Develop and execute a comprehensive data management strategy with governance, standards, and roadmaps.
• Establish data ownership, stewardship, quality, and decision‑making practices.
• Lead design and deployment of scalable cloud data architectures (Snowflake/Azure).
• Build data models, pipelines, integrations, and semantic layers for reporting and analytics.
• Develop Power BI dashboards and reports for business stakeholders.
• Mentor and lead data engineering/analytics teams; manage vendor relationships.

Skills

Data governance

Leadership

Stakeholder management

Analytics

Cloud platforms

Education

Bachelor's degree (Data Science / CS / IS / Engineering)

Tools

Snowflake

Microsoft Azure

Power BI

Job description

Data Management Lead (Oil and Gas Exp. Needed) (JN -092026-430673) Houston, Texas

Salary: USD175000 - USD180000 per year + + Bonus, 401k, Perks

Title: Data Management Lead (Oil and Gas)

Duration: Direct Hire

Location: Onsite, West Houston, TX

Salary Range: $175k + Competitive Bonus + 401k Match

No C2C or 3rd Party Vendors at this time.

Summary

Seeking an experienced Data Management Lead to establish and scale an enterprise data management function supporting business operations, analytics, and strategic decision-making. Oil and Gas experience is highly preferred. This hands‑on leadership role combines data architecture, governance, engineering, and team leadership responsibilities while driving the adoption of modern data platforms and analytics capabilities. The ideal candidate will bring strong experience in data management, cloud technologies, business intelligence, and data governance, along with the ability to bridge technical and business stakeholders.

Responsibilities

• Develop and execute a comprehensive data management strategy, including governance, operating models, standards, controls, and delivery roadmaps.
• Establish roles, responsibilities, and best practices for data ownership, stewardship, quality, and decision‑making across the organization.
• Build and maintain a collaborative, business‑focused culture centered on data quality, transparency, and continuous improvement.
• Design and implement scalable, secure, and maintainable data architectures utilizing Snowflake, Microsoft Azure, and related cloud technologies.
• Develop and manage data models, pipelines, integrations, curated datasets, and semantic layers that support reporting, analytics, and future AI initiatives.
• Ensure data integrity, security, compliance, and governance standards are consistently maintained.
• Lead the deployment, optimization, and support of cloud‑based data platforms and services.
• Develop and enhance Power BI dashboards, reports, and visualizations that provide actionable insights to business stakeholders.
• Partner with IT, cybersecurity, and business teams to ensure secure and efficient access to enterprise data assets.
• Establish and enforce data governance processes covering data quality, ownership, business definitions, access controls, and change management.
• Implement monitoring and remediation processes to improve data accuracy, completeness, consistency, and reliability.
• Collaborate with business leaders and end users to understand reporting and analytics requirements and translate them into scalable solutions.
• Communicate technical concepts, architectural decisions, project updates, and delivery plans to both technical and non‑technical audiences.
• Recruit, mentor, and lead future data engineering, analytics, and AI‑focused team members.
• Manage vendor relationships, external partners, project priorities, budgets, and resource planning.
• Lead data and analytics initiatives from conception through implementation while ensuring alignment with business objectives and operational needs.

Skills

• Bachelor's degree in Data Science, Computer Science, Information Systems, Engineering, or a related field. Oil and Gas industry experience is preferred.
• 10+ years of experience in data management, data architecture, data engineering, analytics, or a related discipline.
• Strong experience designing and supporting enterprise data platforms and modern data architectures.
• Hands‑on expertise with Snowflake, Microsoft Azure, and Power BI.
• Demonstrated experience building or leading data management, analytics, or data engineering functions.
• Strong understanding of data governance, data stewardship, metadata management, data quality, and access controls.
• Experience developing data pipelines, integrations, data models, and enterprise reporting solutions.
• Strong leadership experience including coaching, prioritization, workload management, and performance development.
• Ability to collaborate effectively with business leaders, IT teams, vendors, and external partners.
• Experience supporting analytics, business intelligence, and AI‑driven initiatives.
• Excellent communication, problem‑solving, project leadership, and stakeholder management skills.
• Industry experience supporting complex operational environments is highly preferred.
• Experience with cloud platforms, data security frameworks, and enterprise‑scale reporting environments is preferred.

Success Measures

• Establishment of a scalable and sustainable data management function.
• Improved data quality, governance, accessibility, and trust across the organization.
• Successful delivery of analytics, reporting, and data platform initiatives.
• Increased business adoption of data‑driven decision‑making and self‑service reporting.
• Strong collaboration between business and technology teams with clearly defined data ownership and governance.
• Reliable, secure, and scalable data platforms that support future analytics and AI initiatives.