Data Engineering Lead

Our core values - Stewardship, Character, Collaborate, Learn, Disrupt - are the lens through which we evaluate every business decision. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expands performance among our E&P competitors.

We seek applicants from all backgrounds to ensure we get the best, most creative talent on our team. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply. If you meet any combination of our requirements, we encourage you to apply. We strive to hire people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger.

Job Summary

The Lead Data Engineer is a senior technical role responsible for the design, development, operation, and continuous improvement of Expand Energy's enterprise data platform and data engineering ecosystem. This position owns critical data pipelines, integration frameworks, and enterprise data models that power analytics, reporting, operational processes, data science, and emerging AI capabilities across the organization.

The Lead Data Engineer combines deep expertise in data engineering, data modeling, and data warehousing with strong operational ownership of a modern cloud data platform. This role is responsible for ensuring enterprise data assets remain trusted, scalable, secure, observable, and highly available. In addition to operating and enhancing existing capabilities, this role helps evaluate and adopt emerging platform features that expand the value of enterprise data assets and support the future direction of the Data & Analytics organization.

Job Duties & Responsibilities

• Data Engineering & Integration

• Design, develop, and maintain enterprise data pipelines, integration frameworks, dimensional and canonical data models, and cloud data warehouse solutions that serve as the foundation for enterprise analytics, reporting, machine learning, and AI capabilities.

• Build and operate scalable data pipelines utilizing batch, CDC, streaming, API-based, event-driven, and log-based data movement patterns while ensuring reliability, performance, and data quality.

• Partner with business and technology teams to onboard new data sources, deliver trusted data assets, and establish scalable data engineering solutions aligned with enterprise architecture standards.

• Technical Leadership & Collaboration

• Serve as a lead technical contributor on strategic initiatives that rely on enterprise data assets and integration capabilities.

• Advise project teams on data architecture, integration patterns, platform capabilities, and engineering best practices.

• Mentor data engineers and promote operational excellence across the Data & Analytics organization.

• Collaborate closely with architects, analytics teams, application teams, cybersecurity, infrastructure, and business stakeholders.

• Identify opportunities to leverage emerging data platform capabilities to improve business outcomes and increase organizational agility.

• Balance immediate delivery needs with long-term platform sustainability, scalability, and maintainability.

• Snowflake Platform Ownership

• Support and administer core Snowflake platform capabilities including compute management, resource governance, workload optimization, and security controls.

• Design and maintain role-based access control (RBAC) frameworks and data access patterns supporting enterprise governance requirements.

• Evaluate new Snowflake features and capabilities and recommend adoption strategies where appropriate.

• Help evolve platform capabilities supporting analytics, AI, agentic workflows, semantic models, data products, and future business use cases.

• Engineering Excellence & DevOps

• Establish and promote engineering standards for source control, testing, deployment, documentation, and support.

• Leverage Azure DevOps for backlog management, source control, release management, and deployment automation.

• Perform code reviews and provide technical guidance to other team members.

• Contribute reusable frameworks, templates, utilities, and engineering patterns that improve delivery consistency and speed.

Job Specific Skills

• Advanced SQL development, query optimization, and performance tuning experience.
• Deep understanding of data modeling concepts including dimensional, canonical, normalized, and denormalized data models.
• Strong knowledge of data warehousing principles, cloud data platforms, and modern data architecture patterns.
• Experience designing and supporting enterprise data pipelines, ETL/ELT processes, and data integration solutions.
• Experience developing trusted, reusable data assets that support analytics, reporting, machine learning, and AI use cases.
• Strong understanding of data quality, governance, lineage, and metadata management concepts.
• Strong hands-on experience with Snowflake or a comparable enterprise cloud data platform.
• Experience with modern data integration and transformation technologies such as dbt, Fivetran, Informatica, HVR, Azure Data Factory, or equivalent platforms.
• Experience supporting structured, semi-structured, and unstructured data formats including JSON, XML, Parquet, Avro, and CSV.
• Working knowledge of Snowflake administration, resource governance, role-based access control (RBAC), query optimization, and secure data sharing.
• Familiarity with semantic models, data products, AI-enabled analytics, and emerging cloud data platform capabilities.
• Strong experience utilizing Azure DevOps for source control, backlog management, release management, and deployment automation.
• Experience with Git, pull requests, code reviews, and software development lifecycle best practices.
• Ability to establish engineering standards, reusable frameworks, and development patterns that improve solution quality and delivery consistency.

Education

Minimum: High school diploma or GED

Preferred: Bachelor's degree in Information Systems, Computer Science, or related field

Experience

Minimum: 8 years related work experience

Preferred:

• Snowflake certification (SnowPro Core, SnowPro Advanced, or equivalent).

Expand Energy takes necessary action to ensure that all applicants are treated without regard to their race, color, religion, sex, sexual orientation, age, gender identity, national origin, genetic information, disability, pregnancy, military or veteran status or any other protected characteristic as established by law.

Expand Energy Corporations operations are focused on discovering and developing its large and geographically diverse resource base of unconventional oil and natural gas assets onshore in the United States.