Lead Data Engineer - Cloud Platform

Expand Energy; Spring (TX); On-site; USD 130,000 - 195,000; Full time

Job summary

Expand Energy is seeking a Lead Data Engineer to own the enterprise data platform, pipelines, and modeling. You will drive analytics, reporting, and AI-ready data assets while ensuring security, scalability, and reliability across the data ecosystem.

Key responsibilities include leading data engineering initiatives, mentoring team members, and collaborating with architects, analytics, cybersecurity, and infra teams to advance the Data & Analytics roadmap.

Qualifications

• Advanced SQL development and performance tuning expertise.
• Deep understanding of data modeling concepts (dimensional, canonical, normalized, denormalized).
• Strong knowledge of data warehousing principles and cloud data platforms.
• Experience designing and supporting enterprise data pipelines (ETL/ELT).
• Experience building trusted, reusable data assets for analytics, ML, and AI use cases.
• Familiarity with data quality, governance, lineage, and metadata management.

Responsibilities

• Design, develop, and maintain enterprise data pipelines and cloud data warehouse solutions.
• Lead data engineering initiatives and mentor engineers.
• Advise on architecture, integration patterns, and platform capabilities.
• Balance delivery with long-term platform sustainability and maintainability.
• Oversee Snowflake platform operations, RBAC, and security controls.
• Promote engineering standards, testing, and deployment practices.

Skills

SQL development

Data modeling

Data warehousing

ETL/ELT

Snowflake

Azure DevOps

Data pipelines

RBAC / security

Cloud data platform

Git

Education

Bachelor’s degree in Information Systems or Computer Science

High school diploma or GED

Tools

Python

dbt

Job description

Expand Energy is seeking a Lead Data Engineer to own the enterprise data platform, pipelines, and modeling. You will drive analytics, reporting, and AI-ready data assets while ensuring security, scalability, and reliability across the data ecosystem.

Key responsibilities include leading data engineering initiatives, mentoring team members, and collaborating with architects, analytics, cybersecurity, and infra teams to advance the Data & Analytics roadmap.