Data Engineering Supervisor

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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.

Data Engineering Supervisor

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.

What your day would be like:

You are responsible for:

• 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 Dev Ops/Data Ops.
• Collaborate with stakeholders to translate business needs into technical solutions.
• Champion Agile ceremonies and processes to maximize team velocity and value delivery.

Who we’re looking for:

• 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 Dev Ops practices.
• Familiarity with Oracle Cloud data technologies (e.g., OCI Data Integrator, Oracle Autonomous Data Warehouse).
• Expertise in data modeling (relational, No
  
  SQL, dimensional) and ETL/ELT development.
• Strong SQL and scripting skills for automation and data engineering.

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.

Preferred Special Skills, Knowledge, or Qualifications

• 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 Dev Ops 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, No
  
  SQL, and dimensional modeling.
• Experience with ETL/ELT development and orchestration, Dev Ops/Data Ops concepts.
• Strong SQL and scripting skills for data engineering and automation.

• 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…