Sr Data Solution Engineer

AdobeLehi, UT
$105,700 - $211,850

About The Position

The Digital Transformation and Data Intelligence team is looking for a Senior Data Solutions Engineer. This role will build scalable data products, automation, and AI-enabled solutions that improve how CAO teams operate. This senior individual contributor role requires deep data engineering expertise and strong product thinking. The candidate can turn ambiguous business problems into practical, production-ready solutions. The foundation of the role is data engineering, but the scope extends into APIs, automation workflows, AI-enabled capabilities, and lightweight applications that help teams make better decisions, reduce manual work, and unlock value from data. You will partner with business collaborators, analysts, program leaders, architects, and engineers to translate business needs into scalable solutions. You will also help improve the team’s engineering standards and encourage adoption of modern development practices.

Requirements

  • 7+ years of experience in data engineering, analytics engineering, software engineering, automation engineering, or a related technical field.
  • Strong proficiency in SQL and Python, with experience building reliable data pipelines, data models, APIs, and automated workflows.
  • Experience with cloud data platforms, data warehouses, orchestration tools, Git-based development, and CI/CD practices.
  • Ability to lead complex technical initiatives across multiple systems, partners, and business domains.
  • Strong understanding of data quality, governance, security, access controls, and production reliability.
  • Experience using LLMs or AI-assisted development tools to accelerate engineering work while validating outputs and maintaining quality standards.
  • Strong communication skills, with the ability to explain technical concepts and tradeoffs to technical and non-technical audiences.
  • Bachelor’s degree or equivalent experience in Computer Science, Data Engineering, Information Systems, a related field, or equivalent practical experience.

Responsibilities

  • Develop, build, and support data solutions that scale efficiently, including data streams, schemas, interfaces, and automation workflows.
  • Translate ambiguous business requirements into clear technical solutions and delivery plans.
  • Build automation and intelligent solutions that improve data quality, reduce manual effort, and increase operational capacity.
  • Apply modern engineering practices, including source control, testing, CI/CD, code reviews, documentation, monitoring, and production support.
  • Evaluate, integrate, and optimize data from internal and external systems.
  • Contribute to reusable patterns, engineering standards, and technical direction for data products.
  • Mentor engineers, review designs and code, and help the team effectively use AI-assisted development tools.

Benefits

  • comprehensive benefits programs
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