Oklahoma City, Oklahoma, United States · On-site
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeJOB OVERVIEW The mission of the Data Analytics Engineer at Warwick Energy is to bridge the gap between data engineering and busine…
Skills: SQL, Data Modeling, Power BI, Spotfire, Data Engineering
Oklahoma City, Oklahoma, United States · On-site
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeJOB TITLE: Senior Revenue Accountant – Upstream Oil & Gas JOB LOCATION: Oklahoma City, OK FIRM INTRODUCTION: Warwick Investm…
Skills: Revenue Recognition, Financial Analysis, Account Reconciliations, Upstream Oil & Gas Accounting, Excel Proficiency
Oklahoma City, Oklahoma, United States · On-site
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeFirm Overview Warwick Investment Group is a private equity firm focused on investing in real assets. With approximately $1.5 billi…
Skills: Geologic Interpretation, Well Planning, Geosteering, Reservoir Characterization, Petrophysics
Oklahoma City, Oklahoma, United States · On-site
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeFirm Overview Warwick Investment Group is a private equity firm focused on investing in real assets. With approximately $1.5 billi…
Skills: Geologic Interpretation, Well Planning, Geosteering, Reservoir Characterization, Petrophysics
Oklahoma City, Oklahoma, United States · On-site
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeWarwick Investment Group is a private equity firm focused on investing in real assets. With approximately $1.5 billion in managed …
Skills: Reservoir Engineering, Data Management, ARIES, Spotfire, PowerBI
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The Data Analytics Engineer will bridge the gap between data engineering and business intelligence teams by converting raw data into structured, actionable datasets. They are responsible for designing scalable data models, maintaining robust analytics workflows, and ensuring data accuracy for organizational decision-making.
Candidates must have at least 5 years of experience in the oil and gas industry and deep expertise in SQL and data modeling. Proficiency with BI tools like Power BI or Spotfire and experience with version control systems are required.
Job DetailsLevel: ExperiencedJob Location: Oklahoma City, OK 73116Position Type: Full TimeJOB OVERVIEW
The mission of the Data Analytics Engineer at Warwick Energy is to bridge the gap between data engineering and business intelligence (BI) teams seamlessly. In this role, you will convert raw data into well-structured, accessible datasets and design scalable data models that enable meaningful analytics and reporting.
A critical part of this role involves applying data engineering principles to build and maintain trusted, high-quality data objects within the data warehouse. By ensuring the accuracy, consistency, and reliability of these data assets, you will create a strong foundation for scalable analytics and BI solutions. Your work will enable the organization to leverage a single source of truth for decision-making, fostering confidence in data-driven insights.
As a detail-oriented professional, you will ensure high levels of accuracy and thoroughness in data preparation and documentation. Your problem-solving skills will be essential as you apply analytical thinking to tackle complex challenges in data workflows and in shaping the data.
Collaboration is key in this role, as you will communicate effectively across teams and foster a cooperative working environment. An eagerness for continuous improvement will drive you to learn and implement efficient data solutions and creating robust data products that power BI applications, we encourage you to join our team.
Data Transformation: Bridge data engineering and BI teams to convert raw data into structured, actionable datasets.
Data Modeling: Design scalable data models and semantic layers to optimize BI tool analysis.
Strengthen Data Infrastructure: Collaborate with data engineers to design and maintain robust data models for BI projects.
Workflow Development: Develop and maintain version-controlled analytics workflows using tools like DBT.
Business Alignment: Ensure analytical outputs meet business objectives and are accessible to all users.
Technical Documentation: Create clear documentation for data models, workflows, and analytics solutions for both technical and non-technical stakeholders.
Collaboration: Work with cross-functional teams to support data-driven decision-making and promote best practices in data analytics.
Oil and Gas Industry Experience: At least 5 years of hands-on experience in various aspects of the oil and gas industry, understanding its unique data challenges.
SQL Expertise: Proficient in writing complex SQL queries and designing data models that integrate diverse datasets. Experience with CTEs, advanced formulas, and windowing functions for sophisticated data transformations.
Documentation Skills: Capable of producing clear and detailed documentation for data models, workflows, ELT processes, and analytics solutions to support team collaboration.
Data Modeling Principles: Deep knowledge of data modeling concepts and best practices, including creating semantic layers for BI tools.
BI Tools Experience: At least 5 years of experience in building data models for BI tools like Power BI and Spotfire, understanding data ingestion and transformation for optimal data display.
Collaborative Experience: Proven ability to work effectively with functional business teams, data engineering teams, and analytics teams to align data solutions with business needs.
Scalable Workflows: Proven ability to design and implement scalable workflows and optimize data queries for performance and efficiency.
Version Control Knowledge: Familiar with using version control systems like Git and Azure DevOps to manage and track changes in data models and scripts.
Snowflake and Microsoft Fabric: Proficient in using Snowflake and Microsoft Fabric for data warehousing and management.
Cloud Platforms: Knowledgeable about cloud platforms like Snowflake, Azure, AWS, and GCP for data storage, processing, and analytics.
Python for Data Manipulation: Competent in using Python for data manipulation, analysis, and automation tasks.
Data Governance: Well-versed in data governance principles and compliance requirements, ensuring data quality and security.
Oil and Gas Industry Experience: At least 5 years of hands-on experience in various aspects of the oil and gas industry, understanding its unique data challenges.
SQL Expertise: Proficient in writing complex SQL queries and designing data models that integrate diverse datasets. Experience with CTEs, advanced formulas, and windowing functions for sophisticated data transformations.
Documentation Skills: Capable of producing clear and detailed documentation for data models, workflows, ELT processes, and analytics solutions to support team collaboration.
Data Modeling Principles: Deep knowledge of data modeling concepts and best practices, including creating semantic layers for BI tools.
BI Tools Experience: At least 5 years of experience in building data models for BI tools like Power BI and Spotfire, understanding data ingestion and transformation for optimal data display.
Collaborative Experience: Proven ability to work effectively with functional business teams, data engineering teams, and analytics teams to align data solutions with business needs.
Scalable Workflows: Proven ability to design and implement scalable workflows and optimize data queries for performance and efficiency.
Version Control Knowledge: Familiar with using version control systems like Git and Azure DevOps to manage and track changes in data models and scripts.
Snowflake and Microsoft Fabric: Proficient in using Snowflake and Microsoft Fabric for data warehousing and management.
Cloud Platforms: Knowledgeable about cloud platforms like Snowflake, Azure, AWS, and GCP for data storage, processing, and analytics.
Python for Data Manipulation: Competent in using Python for data manipulation, analysis, and automation tasks.
Data Governance: Well-versed in data governance principles and compliance requirements, ensuring data quality and security.
Founded in 2010, Warwick Investment Group is a SEC-registered investment advisor, managing funds that invest globally in natural resources and real estate. Warwick has an established track record in strategic consolidation in these sectors, having completed more than 4,000 transactions since inception. The firm has ~130 team members and advisors across offices in Oklahoma City, Dallas, New York and London, investing across private equity funds, special purpose vehicles and open-ended structures. The firm also manages capital for pension funds in 8 of the 50 states. The firm aims to generate attractive investment returns across market cycles. Warwick’s in-house data science team works hand-in-hand with Warwick’s sector investment teams over the life cycle of an investment, leveraging innovative technologies to identify market opportunities and optimize investment portfolios. Warwick’s data science team specializes in statistics, econometrics, network analytics and machine learning. Warwick’s real estate platforms specialize in identifying investment opportunities in markets with favorable tailwinds and attractive, risk-adjusted returns. Through consolidation strategies and development, the firm generates alpha through stable and growing yields, inflation protection and value-add returns. Warwick’s energy and natural resources platforms specialize in geology, engineering and investment within each space.
Offices: 3401 Armstrong Avenue, Dallas, TX 75205, US · 6608 N Western Ave, Box 417, Oklahoma City, Oklahoma 73116, US · 5–10 Bolton Street, London, England W1J 8BA, GB · 1330 Avenue of the Americas, Floor 23, New York, NY 10019, US
Founded in 2010, Warwick Investment Group is a SEC-registered investment advisor, managing funds that invest globally in natural resources and real estate. Warwick has an established track record in strategic consolidation in these sectors, having completed more than 4,000 transactions since inception. The firm has ~130 team members and advisors across offices in Oklahoma City, Dallas, New York and London, investing across private equity funds, special purpose vehicles and open-ended structures. The firm also manages capital for pension funds in 8 of the 50 states. The firm aims to generate attractive investment returns across market cycles. Warwick’s in-house data science team works hand-in-hand with Warwick’s sector investment teams over the life cycle of an investment, leveraging innovative technologies to identify market opportunities and optimize investment portfolios. Warwick’s data science team specializes in statistics, econometrics, network analytics and machine learning. Warwick’s real estate platforms specialize in identifying investment opportunities in markets with favorable tailwinds and attractive, risk-adjusted returns. Through consolidation strategies and development, the firm generates alpha through stable and growing yields, inflation protection and value-add returns. Warwick’s energy and natural resources platforms specialize in geology, engineering and investment within each space.
Offices: 3401 Armstrong Avenue, Dallas, TX 75205, US · 6608 N Western Ave, Box 417, Oklahoma City, Oklahoma 73116, US · 5–10 Bolton Street, London, England W1J 8BA, GB · 1330 Avenue of the Americas, Floor 23, New York, NY 10019, US
