Data Solutions Engineer

ONSITE ROLE at LEHI UT


Data pipelines using Python, Airflow, Snowflake, SQL. Enterprise Data Ingestion- Structured & Unstructured file/real time-based data. Advanced AI & LLM Data Prep- Staging data for vector and KG DBs, Data Quality & Validation, DevOps, Security & Compliance


The Digital Transformation and Data Intelligence team is seeking a contract Data Solutions Engineer to build scalable data products, automation, and AI-enabled solutions that improve how CAO teams operate.

This is a hands-on contract role for an experienced individual contributor with strong data engineering skills and a practical, delivery-focused approach. You will take business problems and turn them into production-ready solutions, working within the team's existing engineering standards, patterns, and tooling. The foundation of the work is data engineering, and the scope extends into APIs, automation workflows, AI-enabled capabilities, and lightweight applications that reduce manual work and unlock value from data.

You will work with business collaborators, analysts, program leaders, architects, and engineers to translate business needs into working solutions and deliver them on defined timelines.

Role:

Develop, build, and support data solutions that scale efficiently, including data streams, schemas, interfaces, and automation workflows.
Translate 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.
Deliver work that follows the team's engineering practices, including source control, testing, CI/CD, code reviews, documentation, monitoring, and production support.
Integrate and optimize data from internal and external systems.
Apply established reusable patterns and engineering standards to your deliverables.
Participate in design and code reviews, and use AI-assisted development tools effectively while validating outputs.

Required Skills:

5+ years of experience in data engineering, analytics engineering, software engineering, automation engineering, or a related technical field.
Strong proficiency in SQL and Python, with a track record of delivering reliable data pipelines, data models, APIs, and automated workflows.
Hands-on experience with cloud data platforms, data warehouses, orchestration tools, Git-based development, and CI/CD practices.
Ability to work independently, ramp up quickly, and deliver well-scoped technical work across multiple systems 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 maintaining quality standards.
Strong communication skills, with the ability to explain technical concepts and tradeoffs to technical and non-technical audiences.
Availability for the full contract term and ability to work within existing team processes and tooling.