Data Engineering Supervisor

APS • Phoenix, AZ

34d • Hybrid

About The Position

Our present and future success depends on the creative and dedicated people of our company who demonstrate the principles outlined in the APS Promise: Design for Tomorrow, Empower Each Other and Succeed Together.
At APS, we’re building a modern enterprise data platform that powers analytics, AI, and operational insights across one of Arizona’s most critical industries. As a Data Engineering Supervisor you’ll combine technical leadership with hands-on engineering, guiding a team of data engineers while designing scalable lakehouse architectures, enterprise data models, and high-performance data pipelines.This role is ideal for a technical leader who enjoys solving complex data problems, setting engineering standards, and communicating clearly with both technical and business partners.

Your work will directly support APS’s mission to deliver
safe, reliable, and affordable energy for Arizona.

What You’ll Do:
Partner Across the Business

Manage timelines, prioritize tasks, understanding team dynamics, stakeholder needs, and working across departments.
Align technical solutions with company goals and understanding business metrics
Work closely with analytics teams, architects, and business stakeholders to translate complex business needs into scalable technical solutions.
Communicate technical concepts clearly to both technical and non-technical audiences.

Lead Technical Delivery

Guide a team of data engineers in building and operating enterprise data solutions that support analytics, AI, and operational systems.
Provide hands-on technical leadership in architecture, data modeling, and pipeline design.
Establish engineering standards and best practices across data engineering and DataOps.

Design Scalable Data Architecture

Design and evolve lakehouse architectures and enterprise data models that support governance, performance, and long-term scalability.
Build and optimize ETL/ELT pipelines that deliver trusted, high-quality data to downstream platforms.

Ensure Platform Reliability

Implement DataOps and DevOps practices that support monitoring, automation, and resilient data delivery.
Drive improvements in pipeline reliability, performance, and observability.

Develop Engineers & Foster Healthy Team Dynamics

Coach engineers through design reviews, problem solving, and engineering best practices.
Facilitate constructive technical discussions and navigate competing priorities or technical disagreements to reach strong solutions.
What We’re Looking For:
Effective Communication: Articulating complex technical concepts to non-technical stakeholders, listening to business needs, and clear documentation.
Leadership & Mentorship: Mentoring junior engineers, delegating tasks, and fostering a collaborative team environment.
Problem-Solving & Critical Thinking: Analyzing complex situations, identifying bottlenecks, and proactively solving problems rather than just fixing bugs.
Adaptability & Curiosity: Keeping up with rapidly changing tools and methodologies in the data landscape.
Empathy & Collaboration: Understanding team dynamics, stakeholder needs, and working across departments. Partner effectively with both engineers and business leaders
Ability to facilitate productive conversations when technical perspectives differ

Deep Data Engineering Expertise

Proven experience designing and building enterprise-scale data platforms and pipelines
Strong expertise in data modeling (dimensional, relational, and modern lakehouse patterns)
Advanced SQL and scripting skills used for data transformation, automation, and optimization
Experience with ETL/ELT frameworks and distributed data processing

Data Platform & Cloud Experience

Experience building solutions using modern cloud data platforms
Familiarity with Oracle Cloud Infrastructure (OCI) data services such as:

OCI Data Integrator
Autonomous Data Warehouse

Experience implementing
DataOps, CI/CD, and platform monitoring practices

Technical Leadership

Experience leading engineers or technical initiatives in complex data environments
Ability to conduct architecture reviews, guide design decisions, and enforce engineering standards

Strong candidates demonstrate effective communication skills, technical depth, sound judgment, and the ability to guide teams through complex engineering decisions.Minimum RequirementsLead Data Engineer / Data Engineering Supervisor

Bachelor's degree in Computer Science, Business or other job related field from an accredited college or university
PLUS eight (8) years progressively responsible directly related experience in area/s of assignment is required to obtain an advanced understanding of information and/or communication systems, operating systems, network communications, equipment and infrastructure.
In lieu of Bachelor's degree, a combination of education and experience equaling 12 years is required. Demonstrated leadership skills required.

Requirements

• Bachelor's degree in Computer Science, Business or other job related field from an accredited college or university
• eight (8) years progressively responsible directly related experience in area/s of assignment is required to obtain an advanced understanding of information and/or communication systems, operating systems, network communications, equipment and infrastructure.
• In lieu of Bachelor's degree, a combination of education and experience equaling 12 years is required.
• Demonstrated leadership skills required.
• Proven experience designing and building enterprise-scale data platforms and pipelines
• Strong expertise in data modeling (dimensional, relational, and modern lakehouse patterns)
• Advanced SQL and scripting skills used for data transformation, automation, and optimization
• Experience with ETL/ELT frameworks and distributed data processing
• Experience building solutions using modern cloud data platforms
• Familiarity with Oracle Cloud Infrastructure (OCI) data services such as: OCI Data Integrator Autonomous Data Warehouse
• Experience implementing DataOps, CI/CD, and platform monitoring practices
• Experience leading engineers or technical initiatives in complex data environments
• Ability to conduct architecture reviews, guide design decisions, and enforce engineering standards

Responsibilities

• Lead, mentor, and develop data engineers; manage workload, agile delivery, and vendor engagement.
• Oversee enterprise data lakehouse architecture, ensuring alignment with data governance, domain models, and APS standards.
• Direct data modeling practice across conceptual, logical, and physical layers, including dimensional models, semantic layers, and curated datasets.
• Supervise design and optimization of batch, streaming, and real‑time pipelines; enforce CI/CD, code quality, testing, and observability best practices.
• Collaborate with other departments in the organization to meet data needs.
• Evaluate and integrate new data platform technologies; drive automation, performance improvements, and platform innovation.
• Build strong stakeholder relationships and communicate progress, risks, and architectural decisions.
• Manage team budget, tooling investments, and vendor contracts.
• Familiarity with cloud technologies ( Oracle Cloud Analytics, Oracle Autonomous Data warehouse, OCI Data Integrator etc.).

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees