Oil & Gas Data Analytics Engineer

Ellipsis; Dallas (TX); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

25 days PTO

12 holidays

Life insurance

Short-term disability

Long-term disability

Paid parental leave

Employee Assistance Program

Medical insurance (HDHP)

HSA

FSA

Discretionary 6% 401(k) match

GrubHub lunch credit

Job summary

Ellipsis U.S. Onshore is seeking an Engineering Analyst to support the technical and finance teams in acquisitions, production monitoring, and reserves reporting. You will manage databases, validate data, and build tools to drive outputs for corporate level models.

The role requires collaboration across disciplines, willingness to learn new software, and the ability to adapt in a fast‑paced environment with changing priorities.

Qualifications

• Bachelor’s degree in a related field is required.
• Strong analytical and organizational skills are essential.
• Proficiency in ARIES, Access, and Excel; SQL and Python are a plus.
• Ability to communicate across disciplines and manage multiple projects under deadlines.

Responsibilities

• Support engineering with database management for evaluations.
• Translate type curves and forecast parameters between software.
• Perform data validation and QA/QC across datasets.
• Assist in cash flow analyses, economic evaluations, and internal reporting.
• Build Excel-based tools to support analysis and reporting.
• Prepare data for internal reviews and create insightful visualizations.

Skills

Strong analytical skills

Good organizational skills

Ability to communicate across discs

Willingness to learn new tools

Proven track record of handling multi‑

Education

Bachelor’s degree in computer science, math, physics, engineering, or related field

Tools

ARIES

Access

Microsoft Excel

SQL

Python

Macros in Office

Job description

Ellipsis U.S. Onshore is seeking an Engineering Analyst to support the technical and finance teams in acquisitions, production monitoring, and reserves reporting. You will manage databases, validate data, and build tools to drive outputs for corporate level models.

The role requires collaboration across disciplines, willingness to learn new software, and the ability to adapt in a fast‑paced environment with changing priorities.