Technology Enablement Engineer

SM-Energy Company•Denver, CO

2d•$140,000 - $180,000

About The Position

The Technology Enablement Engineer works across every department at SM Energy to design, build, and operationalize analytics, automation, and AI solutions in our technology stack, while enabling business users to extend and maintain those solutions themselves. This role combines hands-on engineering — data pipelines, data models, dashboards, and AI workflows — with the technical mentorship that creates lasting self-sufficiency. The Engineer has a deep understanding of computer capabilities and the interfaces between analytic, automation, and AI applications and applies that knowledge to architect reliable, scalable, and well-tested solutions. The engineer will translate complex concepts for both technical and non-technical audiences. Acting as a trusted liaison between the business units, technology, and support teams, the Engineer resolves technical issues, right-sizes tools to problems, and raises the engineering rigor of solutions built across the organization. With a strong emphasis on the responsible delivery and adoption of AI, this individual works closely with the Data, Analytics Applications, GIS, and Enterprise Delivery teams to advance analytic and AI maturity and drive a data-first, AI-native culture across the organization.

Requirements

Minimum of 5 years of related experience in analytics engineering, data engineering, AI/ML solution delivery, business intelligence, analytics enablement, or a related discipline.
Working-to-proficient knowledge across the analytics, automation, and AI tool stack the team supports — sufficient to build production solutions, review business-built solutions, teach others, and advise on appropriate tool selection.
Claude and Claude Code— prompting strategy, Claude Connectors, deployment patterns, and responsible AI use; the primary platform for AI enablement delivery.
Python— scripting, data manipulation, and automation for custom BI/automation solutions and data wrangling; sufficient to teach and review business-built code.
SQL— querying, data preparation, and translating business needs into data logic.
Power BI— report and dashboard development, data modeling fundamentals, and citizen-developer support.
Spotfire— analytics delivery in upstream and operational contexts.
Metabase— self-service reporting and data exploration; enabling business onboarding and use-case scoping.
Alteryx— workflow-based data preparation and automation.
Power Automate / Power Automate Desktop— business process and desktop automation.
Azure DevOps— version control, work tracking, and agile / sprint-based delivery.
Technical Engineering & Enablement: Skilled at building reliable, scalable solutions and at explaining technical concepts to both technical and non-technical audiences. Applies engineering rigor and adult-learning principles to deliver solutions and build lasting capability in others.
Communication & Interpersonal Savvy: Friendly and approachable, effective across diverse styles and position levels, and able to adjust the message to fit the audience while building rapport and trust.
Collaborates & Customer Focus: Builds collaborative relationships across every business unit, listens to understand, and delivers enablement that meets and exceeds stakeholder expectations.
AI Fluency & Responsible AI: Passionate about the practical, responsible use of AI; able to build governed, effective AI solutions using Claude and Claude Code, curate high-quality data sets for AI systems such as WellBuddy, and rigorously validate AI-generated output.
Tech Savvy & Strategic Mindset: Anticipates the impact of emerging technologies, learns and adopts them quickly, and connects enablement work to broader business strategy.
Manages Ambiguity & Cultivates Innovation: Deals comfortably with change and uncertainty, moves beyond traditional thinking, and champions creative solutions through a continuous-improvement mindset.
Security Mindset: Proactively identifies and communicates cybersecurity, data privacy, and governance risks, and models cyber-hygiene best practices for the business.
Business Acumen: Understands SM Energy's business drivers and applies that context when prioritizing enablement and guiding stakeholders toward the right solutions.
Drives Results & Resilience: Action-oriented and dependable, accomplishing objectives despite obstacles and maintaining a positive, can-do attitude in a fast-changing environment.

Nice To Haves

Oil and gas experience is preferred.

Responsibilities

Teach and coach business users across all departments how to build robust, scalable, and sustainable analytics and automation solutions in our tech stack — building capability in others rather than building the solutions for them.
Partner with the Technology Enablement Lead to build reusable frameworks, templates, and reference architectures — along with the training, workshops, and 1:1 technical support — that enable self-service data discovery, analytics, automation, and data science across the business.
Champion the delivery and responsible adoption of AI across the enterprise — building and configuring prompting strategies, Claude and Claude Code integrations, connectors, and governed AI workflows for users at every skill level.
Assist in generating and curating high-quality data sets that power SM Energy's internally developed AI chat assistant — designing, structuring, cleaning, and validating the curated data and semantic layers that ground the model's responses, and ensuring the underlying data is accurate, well-documented, and fit for AI consumption.
Partner with data owners and subject-matter experts to identify authoritative sources, resolve data conflicts, and continuously improve the accuracy and coverage of the curated data sets that WellBuddy and other AI solutions rely on.
Lead design and code reviews, defining requirements, acceptance criteria, and engineering standards so that solutions are effectively architected, developed, and tested prior to production release.
Establish and enforce rigorous testing and validation practices to ensure the accuracy of data transformations, calculations, and visualizations — defining test cases, reconciling outputs against trusted source-of-truth data, and documenting validation results before any solution is released to production.
Build automated data-quality checks, regression tests, and validation frameworks that continuously monitor accuracy and flag data or model drift, reinforcing data governance and quality across the Data & Analytics department and the business as a whole.
Develop and review SQL and Python for custom BI and automation solutions and data wrangling, elevating the engineering capability of the business through pairing, code review, and reusable tooling.
Advise on tool selection and platform right-sizing, matching each business problem to the right tool at the right complexity level (Claude, Power BI, Spotfire, Metabase, Alteryx, Python, and Power Automate).
Mentor junior team members and business users providing technical guidance and direction that helps others deliver fast, reliable analytics and automation.
Engineer and model data security and privacy best practices; identify sensitive data sets and design secure, compliant solutions.
Act as a friendly, approachable partner to every department, building trusted, collaborative relationships and seeking win-win, mutually beneficial outcomes.
Operate successfully in an agile / sprint-based approach, prioritizing enablement work across multiple departments and initiatives.
Proactively identify capability gaps, risks, and opportunities, and recommend training, technologies, and ways of working to close them.
Contribute to technical research, benchmarking, and recommendations for emerging AI and analytics platforms and ways of working.
Demonstrate a commitment to continuous learning by staying current with our tech stack and the evolving AI landscape, and by actively engaging in development communities to share experiences and knowledge.