Description

Position Purpose and Objectives:

This position acts as the builder and engineer behind United Power's data platform, transforming raw data into structured, reliable, and accessible information for use across the organization. Azure Databricks sits at the center of this work, serving as the primary platform for storing, transforming, and delivering data across the organization.

Reporting to the Data Engineering Manager, this position is part of a small, close-knit team with an outsized impact on how United Power uses its data.

This is a hybrid position, eligible to work primarily remote, subject to the United Power hybrid work agreement. On-site work may require the incumbent to report to any United Power location with little notice, depending on business needs and projects.

Essential Functions and Responsibilities:

Data Engineering & ETL Delivery

• Design, build, and maintain ETL/ELT pipelines that automate the movement of data between systems, applications, and external organizations.
• Develop deep working knowledge of United Power's data sources, including customer and billing data, financial data, meter data, and electrical system data, and how that data needs to move and transform to serve downstream users and tools.
• Build and maintain data lake, delta lake, and data warehouse structures, including Medallion (Bronze/Silver/Gold) architecture, that store and organize data efficiently for use across the organization.
• Transform and structure data so it is accessible, well-organized, and usable by the business intelligence tools, analysts, and applications that depend on it.
• Build monitoring and alerting into data pipelines to proactively detect data quality issues such as breakages, schema drift, or anomalies, and surface findings to the Data Engineering Manager, Data Enablement program, or relevant business units for resolution.
• Acquire data from primary and secondary sources in the most efficient and reliable manner available.

Platform Administration

• Support the administration of United Power's Azure Databricks environment, including workspace configuration, cluster management, and Unity Catalog governance, commensurate with level.
• Support the administration and maintenance of Azure Data Factory pipelines and orchestration for enterprise data integration needs.
• Build and maintain Lakeflow Spark Declarative Pipelines and Declarative Automation Bundles to support reliable, repeatable deployment and orchestration of data workflows.
• Support the administration of Azure storage accounts (data lakes), including data lifecycle management policies for data retention, tiering, and cost optimization.
• Maintain working knowledge of Databricks' AI/ML tooling and broader industry trends, applying that knowledge to data architecture and pipeline design decisions.
• Assist in evaluating new tools, technologies, and platform features that could enhance the team's data engineering capabilities.
• Partner with the Cybersecurity and Infrastructure teams to implement appropriate access controls, security configurations, and data protection standards within the platform.

Collaboration & Accountability

• Build strong working relationships with stakeholders across the business to understand their data needs and how business processes are reflected in the data.
• Collaborate effectively with IT Infrastructure Engineers on the implementation and maintenance of infrastructure supporting data solutions.
• Actively support ITIL-based change, problem resolution, and incident management practices.
• Accept accountability for all areas of responsibility and hold peers accountable.
• Participate in an on-call rotation as needed to support critical data platform issues.

Secondary Functions and Responsibilities:

• Creates, expands, and maintains professional and productive working relationships with peers and stakeholders. Works collaboratively with colleagues and fosters a spirit of cooperation and inclusion in the workplace.
• Performs other such duties as may be requested or assigned to fulfill the needs of United Power in the interest of good management practice.

Progression and Proficiency:

The Data Engineer class series consists of three positions: Data Engineer I, II, and III. Positions in this series are flexibly staffed; placement and advancement are based on demonstrated proficiency across the roles' core skills and focus areas, not solely on tenure.

Expected Proficiency Mapping:

Engineer I: Primarily operates at the Practitioner level (building mastery).

Engineer II: Primarily operates at the Journey level (autonomous and mentoring).

Engineer III: Primarily operates at the Expert level (strategic and innovative).

Proficiency levels are defined as:

Novice

• Possesses a basic understanding of tasks in this sphere and can perform them with some or no support in a relatively low-pressure environment.

Practitioner

• Demonstrates an advanced understanding of issues and topics in this sphere.
• Able to operate effectively under time constraints and pressure, with minimal or no assistance.
• Implements strategies and tactics to achieve goals and can adapt and improvise when necessary.

Journey

• Capable of operating effectively in conditions of uncertainty and stress.
• Willing and able to improve the skills of Novices when requested.
• Able to evaluate and implement new ideas proposed by Practitioners.
• Contributes to the development of best practices and standards within the sphere.

Expert

• Able to perform complex tasks in conditions of high uncertainty, stress, and conflict, within tight timeframes and with minimal or no mentorship.
• Demonstrates strong collaborative leadership skills and can effectively lead small teams.
• Innovates and introduces new ways of working, organizing, and teaching, and actively shares knowledge with those who are willing to learn.
• Recognized as a thought leader and expert within the organization for topics in this sphere.

Core Skills and Required Knowledge:

• Demonstrated aptitude and enthusiasm for learning new technologies, with curiosity and the ability to formulate questions when identifying and evaluating solutions or researching problems.
• Ability to work both independently and collaboratively, and as a member of a team.
• Ability to work independently based on general and specific direction, project task assignments, and department priorities. Day-to-day work is self-initiated and self-directed.
• Ability to organize and drive own daily activities based on both broad and specific directives, processes, and procedures, with the ability to meet multiple deadlines and effectively handle multiple tasks.
• Ability to collaborate with others to participate in root cause analysis and solve problems both within and outside the area of technical expertise.
• Diagnose and resolve complex technical problems independently within areas of technical expertise.
• High level of customer service ethic, with empathy for data users across the organization.
• Strong written and verbal communication skills, with the ability to tailor technical communication to the recipient's level of technical fluency.
• Ability to create, expand, and maintain productive working relationships with peers and stakeholders.

Focus Area: ETL/ELT Pipeline Development

Designing, building, and maintaining the pipelines that automate the movement and transformation of data between systems, applications, and external organizations. Key skills include pipeline orchestration, data transformation techniques, and Multispeak, a protocol commonly used for integrating utility industry systems.

Focus Area: Databricks & Data Platform Administration

Administering and supporting United Power's Azure Databricks environment, including workspace configuration, cluster management, and governance. Key skills include Unity Catalog, Lakeflow Spark Declarative Pipelines, Declarative Automation Bundles, and Azure Data Factory.

Focus Area: Data Modeling, Storage & Architecture

Designing and organizing the structures that store and deliver data efficiently across the organization. Key skills include data lake and delta lake architecture, Medallion (Bronze/Silver/Gold) design, and data warehousing.

Focus Area: Programming & Scripting

Writing clean, efficient, and maintainable code, including through the effective use of AI-assisted development tools, to support data pipelines, automation, and infrastructure-as-code. Key skills include Python, SQL, Terraform (HCL), querying relational databases such as Oracle and Microsoft SQL Server, and integrating with vendor-provided APIs.

Supervision Received and Exercised:

Receives both general and specific guidance and direction from the Data Engineering Manager and/or the CIO.

Education, Training and Experience:

Data Engineer I/II/III

Equivalent to graduation from a four-year college or university with major coursework in computer science, information systems, or a closely related field. Equivalency may be demonstrated through a combination of training and progressively responsible experience that resulted in the required specialized knowledge and abilities to perform the assigned work in lieu of a degree.

Data Engineer II

AND a combined 3 years of advanced, hands-on technical engineering experience in technologies relevant to the position, including cloud-based data platforms such as Azure Databricks.

Data Engineer III

AND a combined 6 years of advanced, hands-on technical engineering experience in technologies relevant to the position, including cloud-based data platforms such as Azure Databricks.

Problem Solving: Ability to collaborate with others to participate in root cause analysis and solve problems both within and outside the area of technical expertise, diagnosing and resolving technical problems independently, with the complexity and independence expected increasing at higher levels.

Discretion/Latitude: Works independently and as a member of the data engineering team, based on general and specific direction, project task assignments, and department priorities. Day-to-day work is self-initiated and self-directed based on priorities established by the Data Engineering Manager or the CIO, with the degree of independent direction expected increasing at higher levels.

Impact: This position is a critical component of the engine powering United Power's data infrastructure, directly building and maintaining the pipelines and platforms that transform raw, disparate data into a reliable, well-structured foundation the organization depends on. By working hands-on within a growing Azure Databricks environment, the Data Engineer helps ensure that the Data Engineering Manager's vision for the platform becomes reality, and that the Data Enablement program and every team relying on trusted data, from analytics and reporting to future AI-driven initiatives, can do so with confidence. This role ensures that United Power's data is accurate, accessible, and dependable, providing a solid technical foundation for the organization's operational and strategic decisions.

Liaison: This role requires maintaining strong working relationships across three key spheres: technical, business, and vendor. The Data Engineer works closely with the Data Engineering Manager and fellow data engineers to deliver technical solutions, and collaborates with the Cybersecurity and Infrastructure teams to ensure data platforms are secure and well-integrated. This position also partners with the Data Enablement program and business stakeholders across the organization to understand data needs and deliver data-driven value. Additionally, this role interfaces with data engineering platforms and technology vendors to support the tools and systems that underpin United Power's data platform.

Essential Physical and Mental Requirements:

• Majority of time requires sitting, bending at neck, waist, legs, and arms; twisting body; and changing positions at will. Occasional driving, standing, walking, stooping, bending, kneeling, reaching, and stooping.
• Requires repetitive motions with hands and fingers such as keyboarding, use of telephones, cell phones, etc.
• Requires close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to focus.
• Noise level in work environment is moderate. Work requires close attention to detail and accuracy, is varied in nature, and involves regular interruptions. Work is subject to irregular hours.

Working Conditions:

Office setting ninety-five percent (95%) of the time. Five percent (5%) of the time may need to work in a support role while outdoors, in a warehouse, or in a maintenance environment (dust, uneven surfaces, and all types of weather and temperature variations).

Department: Information Services FLSA Status: Exempt Updated: July 2026

Typical hiring range:

Level I: $97,700 - $114,150 annually. Position is withing a grade with a maximum of $130,600

Level II: $107,000 - $127,900 annually. Position is within a grade with a maximum of $148,800

NOTE: This position description is not intended to be all-inclusive; an employee will also perform other job responsibilities as assigned by the immediate supervisor or management. Management reserves the right to change position descriptions, specifications, or work schedules to accommodate individuals with disabilities or as needed. This position description does not constitute a written or implied contract of employment.