Director, Software Engineering and Enterprise Analytics

Venture Global LNG•Arlington, VA

4h•Onsite

About The Position

Venture Global LNG (“Venture Global”) is a long-term, low-cost provider of American-produced liquefied natural gas. The company’s two Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global’s modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost. Position Overview Venture Global LNG is seeking an experienced Director of Software Engineering and Enterprise Analytics to lead the execution and operationalization of analytics, AI, ML, and software solutions. Reporting to the Vice President of Software Engineering and Enterprise Analytics, the Director will be responsible in executing and delivering analytics and software products aligned to VP-defined strategic priorities. The Director will lead and manage teams of software engineers, data scientists, and analytics professionals, with direct accountability for the execution, quality, and delivery of enterprise software, analytics, and AI solutions. This role is deeply involved in architectural decisions, implementation oversight, and production deployment, ensuring solutions meet performance, security, and reliability standards. Working closely with business stakeholders, the Director converts defined strategy and priorities into executable roadmaps, driving disciplined delivery and operational excellence across engineering and analytics teams.

Requirements

Bachelor's degree in Computer Science, Information Technology, Data Science, Engineering, or related discipline; Master's degree preferred.
Minimum of eight (8) years of progressive experience in software engineering, enterprise analytics, or related technical leadership roles, including at least two (2) years in leadership or management capacity.
Proven track record leading software, analytics, and Al teams within complex, high-growth, or industrial environments.
Experience deploying enterprise-scale solutions integrating software development, data analytics, and cloud platforms.
Demonstrated expertise in application architecture, machine learning, and business intelligence platforms.
Exceptional communication, team-building, and executive stakeholder management skills. Strong business acumen and ability to translate technology investment into business outcomes. Demonstrated commitment to diversity, equity, and inclusion.

Responsibilities

Own the execution and delivery of enterprise analytics, AI/ML, and software initiatives aligned to VP‑defined roadmaps.
Ensure AI and ML models are deployed, monitored, and operationalized in production environments.
Own end‑to‑end execution from backlog definition through deployment and monitoring.
Drive predictable delivery through disciplined planning, execution tracking, and risk management.
Establish and reinforce execution standards across data engineering, data science, machine learning engineering, software engineering, and business intelligence teams.
Lead the day‑to‑day delivery of business intelligence, advanced analytics, AI, and machine learning solutions supporting operations.
Step in directly during critical delivery issues, production incidents, or performance degradation.
Oversee data engineering pipelines, model lifecycle management, and analytics platforms in a cloud‑first Azure/Databricks environment.
Partner with stakeholders to ensure analytics solutions are trusted, adopted, and embedded in business workflows.
Support the continued maturation of data governance, data quality, and metadata management practices.
Actively participate in code reviews, data pipeline design, model validation, and production readiness reviews.
Ensure solutions are secure, scalable, performant, and compliant with enterprise and regulatory standards.
Collaborate with architecture, security, and infrastructure teams to mitigate delivery and compliance risk.
Balance innovation with operational stability in a regulated, industrial environment.
Manage and develop a technical team across engineering and analytics disciplines.
Coach and support managers to drive high performance, accountability, and continuous improvement.
Foster a culture that values execution discipline, innovation speed, and business partnership.
Support talent development and performance management.
Facilitate stakeholder workshops to define technical requirements and solution architecture.