Data Engineering Supervisor

APS•Phoenix, AZ

4d•Hybrid

About The Position

At APS, we’re building a modern data ecosystem to power innovation and deliver insights that matter. As a Data Engineering Supervisor on our Data Platform & Delivery Team, you’ll lead the design and operation of cutting-edge lakehouse architectures, enterprise data models, and data pipelines. Your work ensures reliable, high-quality data capabilities that fuel analytics, AI, reporting, and operational workflows—helping APS achieve its mission of safety, reliability, and affordability.

Requirements

Proven success leading technical teams and delivering enterprise-scale data solutions.
Ability to design scalable, governed architectures aligned with business needs.
Strong communication and collaboration skills with a customer-centric mindset.
Skilled in Agile delivery and DevOps practices.
Familiarity with Oracle Cloud data technologies (e.g., OCI Data Integrator, Oracle Autonomous Data Warehouse).
Expertise in data modeling (relational, NoSQL, dimensional) and ETL/ELT development.
Strong SQL and scripting skills for automation and data engineering.
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.

Nice To Haves

Demonstrated success leading engineering teams/equivalent technical teams and delivering enterprise‑scale data solutions.
Ability to translate business needs into scalable, governed architectural solutions.
Strong communication, stakeholder partnership, and cross‑functional collaboration skills.
Takes a customer-centric approach to problem solving;
Skilled in agile delivery and DevOps practices.
Familiarity with Oracle Cloud data technologies (preferred) like OCI Data Integrator, Oracle Autonomous Data warehouse, etc..
Understanding of data warehousing/lakehouse patterns, medallion architecture and modern analytical architectures.
Familiarity in data modeling (conceptual, logical, physical), including relational, NoSQL, and dimensional modeling.
Experience with ETL/ELT development and orchestration, DevOps/DataOps concepts.
Strong SQL and scripting skills for data engineering and automation.
Familiarity with cloud technologies ( Oracle Cloud Analytics, Oracle Autonomous Data warehouse, OCI Data Integrator etc.).

Responsibilities

Lead a team of data engineers to deliver enterprise-scale data solutions using Agile practices.
Design and optimize lakehouse architecture and enterprise data models for scalability and governance.
Develop and maintain robust data pipelines supporting analytics, AI, and operational workflows.
Drive platform reliability and implement best practices in data engineering and DevOps/DataOps.
Collaborate with stakeholders to translate business needs into technical solutions.
Champion Agile ceremonies and processes to maximize team velocity and value delivery.
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.