Lead Data Engineer

Idaho Power Company•Boise, ID

9h•$134,992 - $162,573•Onsite

About The Position

Idaho Power is seeking a Lead Data Engineer, also referred to as a Lead Data Solutions Developer, to join its Information Technology team in Boise, Idaho. The role provides enterprise-level technical direction for data platforms, solutions, and engineering practices that support trusted analytics, operational decision-making, and emerging artificial intelligence capabilities. The Lead Data Engineer stewards architecture, defines standards and reusable patterns, guides platform modernization, and translates strategic business needs into scalable, governed, secure, and sustainable data solutions. The role provides leadership through technical direction, coaching, mentoring, facilitation, and influence across teams, without direct reports. The position is exempt and regular. Idaho Power describes its work as supporting safe, reliable, and affordable energy for communities in Idaho and Oregon. The company offers work-life balance, competitive pay and benefits, an employee incentive plan, a 401(k) employer match, and a pension plan.

Requirements

Bachelor's degree in computer science, information systems, data science, engineering, or a related field, or an equivalent combination of education and experience.
At least 8 years of experience in data engineering, business intelligence, cloud data platforms, data architecture, database development, or a related discipline.
Knowledge of enterprise data architecture, integration patterns, dimensional modeling, and modern cloud data platform design.
Knowledge of ETL/ELT, orchestration, and data-processing technologies; Medallion, Lakehouse, and Warehouse architecture patterns; and data governance, metadata, lineage, quality, stewardship, and information lifecycle practices.
Knowledge of data security and access control, and software development lifecycle practices including Agile, source control, automated testing, and CI/CD.
Advanced SQL and Python development, database design, query optimization, and performance tuning skills.
Ability to design scalable pipelines, integration frameworks, reusable components, and orchestration solutions.
Ability to evaluate platform capabilities, architectural tradeoffs, technical risks, and emerging technologies.
Experience or skills in Azure DevOps, Git, automated testing, deployment automation, and CI/CD.
Executive and technical communication, consensus building, mentoring, and management of competing priorities.
Ability to provide enterprise-level technical leadership; translate strategic objectives into scalable, secure, reliable, maintainable, and cost-effective solutions; influence decisions; communicate across varied audiences; guide modernization; and drive continuous improvement.

Nice To Haves

Knowledge or experience with utility industry systems, regulations, business processes, or data domains.
Hands-on experience with Microsoft Synapse, Microsoft Fabric, Azure Data Factory, Power BI, or comparable enterprise data and analytics technologies.
Ability to apply knowledge of utility systems, regulations, business processes, and data domains to enterprise data strategy and solutions.

Responsibilities

Provide enterprise-level technical leadership and direction for data platforms, solutions, and engineering practices.
Steward data architecture and define technical standards, reference architectures, and reusable patterns.
Guide platform modernization and translate strategic business needs into scalable, governed, secure, and sustainable data solutions.
Balance business value, architecture, security, performance, cost, and delivery risk when shaping solutions.
Lead architecture, design, and code reviews and resolve complex production, data quality, performance, and systemic issues.
Influence decisions, build consensus, and communicate strategies, risks, and recommendations to varied audiences.
Coach and mentor engineers and provide technical direction across teams without direct reports.
Anticipate future needs, drive continuous improvement, and remain accountable for the health and evolution of enterprise data capabilities.