Data Quality & Automation Engineer

PNC

Pittsburgh (Allegheny County)

On-site

USD 110,000 - 170,000

Full time

3 days ago
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Job summary

PNC seeks a Technology Engineer in its Data and Automation organization to design and maintain enterprise data quality platforms across Pittsburgh, Cleveland, Dallas, or Birmingham. You will partner with Product Owners and platform teams to ensure scalable, auditable data quality solutions that align with business and risk objectives.

Responsibilities include architecture decisions, governance needs, and strong documentation practices, with emphasis on non-functional requirements and

Qualifications

  • Strong knowledge of data quality frameworks and governance.
  • Understanding of metadata and lineage concepts.
  • Analytical problem solving across multi-platform data environments.
  • Ability to document architecture decisions and technical standards.
  • Experience with Agile/SAFe, SQL, and testing practices.

Responsibilities

  • Owns design of enterprise data quality platforms and tooling for governance and auditable monitoring.
  • Focuses on platform and capability design rather than traditional ETL development.
  • Evaluates data platforms and integration patterns for fitness of purpose.
  • Translates requirements into technical architecture decisions with scalability and reliability in mind.
  • Documents architecture decisions and technical standards for long-term sustainability.

Skills

Data quality frameworks
Metadata/lineage fundamentals
Analytical problem solving
Technical documentation
Agile/SAFe
SQL
Testing experience

Job description

PNC seeks a Technology Engineer in its Data and Automation organization to design and maintain enterprise data quality platforms across Pittsburgh, Cleveland, Dallas, or Birmingham. You will partner with Product Owners and platform teams to ensure scalable, auditable data quality solutions that align with business and risk objectives.

Responsibilities include architecture decisions, governance needs, and strong documentation practices, with emphasis on non-functional requirements and

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