Data Solutions Engineer

The Digital Transformation and Data Intelligence team is looking for a Data Solutions Engineer. This role will build scalable data products automation and AI-enabled solutions that improve how CAO teams operate.

This 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 teams engineering standards and encourage adoption of modern development practices.

• 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.

• 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.
• Bachelors degree or equivalent experience in Computer Science Data Engineering Information Systems a related field or equivalent practical experience.

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