Job Description

The Dolese Promise is built on a foundation of integrity driven by our passion for quality, safety, and reliability. We are one of Oklahoma's most respected employee-owned companies because of our people and our values. We strongly believe in positively impacting our communities through our products, our actions, and our financial support.

Being a part of the Dolese team affords a unique opportunity to join an organization that rewards its owners through profit sharing. Our employees are one of our most important resources, which is why we promise to deliver.

Dolese Delivers:

• Stable Foundation
• Treat with Respect
• Safe Environments
• Employee Focus

JOB SUMMARY

Grow your career with a company built on Safety, Integrity, Teamwork, and Stewardship. As a Data Engineer at Dolese, you will play a key role in transforming data into actionable insights that support business and operational decision-making across the organization. This role is responsible for applying advanced analytics techniques, data modeling, dashboard/report development, and collaborating with business partners to identify opportunities for performance improvement. The Data Engineer supports the organization’s analytics capabilities by applying established machine learning and statistical techniques within business intelligence workflows, contributing to data quality and reporting improvements, and supporting analytics initiatives.

WHY JOIN US

We are people, building communities from the ground up. For our employees, we are focused on building careers. Joining our team means:

• Stability & Legacy: Be part of a company with more than a century of success, operational excellence, and a strong commitment to our employees.

• Growth Opportunities: Expand your analytics expertise by applying advanced analytics, data modeling, and applied machine learning techniques while deepening your business partnership skills and exposure to enterprise BI and analytics platforms.

• Impactful Work: Your contributions help improve data quality, reporting, and decision-making, enabling teams across the organization to operate more efficiently and make informed business and operational decisions.

• Supportive Culture: Our employees support one another and our customers through our service values: Champion Kindness, Incite Enthusiasm, Build Relationships, and Provide Innovative Solutions. We value collaboration, integrity, and continuous improvement.

KEY RESPONSIBILITIES/ESSENTIAL FUNCTIONS

Advanced Analytics & Insight Generation

• Analyze complex datasets to uncover trends, patterns, and opportunities that drive strategic and operational decisions.

• Apply predictive models, approved machine learning techniques, and statistical analyses to forecast outcomes, support scenario planning, and enhance business intelligence.

• Translate analytical findings into clear, compelling insights and recommendations for business stakeholders.

• Leverage AI-assisted tools (e.g., Copilot, generative AI, natural language query) to accelerate insight discovery and enhance self-service BI capabilities for business users.

Data Modeling & Data Management

• Develop, refine, and maintain semantic models, datasets, and curated data structures used for reporting, analysis, and supporting machine learning use cases.

• Support enterprise data governance by ensuring accuracy, consistency, and quality across analytics assets.

• Collaborate with data engineering teams to improve data pipelines, definitions, and reliability, and support scalable data architecture that enables BI and analytics workloads.

Reporting & Dashboard Development

• Build and maintain enterprise dashboards and reports using tools such as Power BI, Tableau, or similar platforms.

• Ensure visualizations follow best practices for clarity, usability, and performance.

• Continuously enhance existing reports based on stakeholder feedback and evolving business needs.

• Integrate AI-powered features into BI platforms, such as anomaly detection, intelligent alerting, and ML-driven forecasting embedded in dashboards.

Business Partnership & Stakeholder Engagement

• Work closely with business leaders to understand their objectives and translate them into analytic requirements.

• Partner with business stakeholders to provide guidance on KPIs, metrics, and measurement strategies that support informed decision-making.

• Clearly communicate complex analytical results to non-technical audiences.

Continuous Improvement & Mentorship

• Provide informal guidance and knowledge sharing to other analysts on analytical methods, AI/ML techniques, BI tools, and best practices.

• Support continuous improvement of analytics processes, including automation, documentation, and standardization.

• Contribute feedback to established analytics standards, templates, and frameworks.

QUALIFICATIONS

Education & Experience

• Bachelor’s degree in Data Analytics, Statistics, Computer Science, Business, Engineering, or related field required; Master’s degree in Data Science, Analytics, Statistics, or related field preferred.

• Minimum of four (4) years of hands-on analytics experience working with large or complex datasets.

• Strong working knowledge of SQL and data querying, data visualization tools (Power BI strongly preferred), analytical/BI tools, data modeling concepts, and foundational ML/AI concepts.

• Strong understanding of data warehousing, ETL/ELT concepts, relational and columnar database structures, and established modern data architecture patterns (e.g., data lakehouse, medallion architecture) used to support analytical workloads.

• Experience with cloud analytics platforms such as Azure Synapse, Databricks, or Snowflake preferred.

• Proficiency in Python or R for advanced analytics, applied machine learning use cases, or automation preferred.

• Familiarity with libraries such as scikit-learn, pandas, or statsmodels preferred.

• Hands-on experience applying predictive modeling and machine learning techniques (e.g., regression, classification, clustering, time-series forecasting) to business intelligence use cases preferred.

• Familiarity with MLOps concepts, model monitoring, and AI governance practices as related to supporting reliable deployment of ML models in production BI environments preferred.

• Industry experience in energy, manufacturing, healthcare, or customizable services preferred.

Knowledge, Skills & Abilities

• Ability to translate business needs into effective analytical solutions that drive insight and decision-making.

• Strong analytical mindset with strong critical thinking skills.

• Excellent communication and data storytelling abilities.

• Proven ability to build effective stakeholder partnerships that align analytics to business needs.

• Demonstrated technical curiosity and continuous-learning mindset, with active interest in emerging AI/ML and BI technologies.

• Proven attention to detail and commitment to high standards for accuracy.

• Ability to manage multiple priorities in a fast-paced environment while maintaining focus and quality.

• This position is hybrid, with a mix of onsite and remote work. The schedule generally includes regular onsite collaboration and flexibility for remote work based on role and business needs.

• May involve occasional extended hours during major reporting cycles or project deadlines.

PHYSICAL REQUIREMENTS

• Ability to lift, push, or pull objects of various dimensions up to 30 lbs. of weight occasionally.

• Ability to perform primarily sedentary work and tolerate prolonged standing, sitting, and walking.

• Ability to perform repetitive motions such as typing and data entry using a keyboard and mouse.

• Ability to communicate clearly and effectively.

EEO Statement:

We consider applicants for all positions without regard to race, color, religion, sex, national origin, age, genetics, marital or protected veteran status. Dolese provides 'reasonable accommodations' to qualified individuals with disabilities in accordance with the American with Disabilities Act and applicable state and local laws. If you need a reasonable accommodation in order to complete the application process please contact the Human Resources Director.