Data Engineer IV – AI & Data Products

Data Engineer IV – AI & Data Products

(Draper UT, In-Office)

• Define, build, validate and maintain domain‑specific data product assets and data pipelines.
• Collaborate with analytics and business partners to define and build semantic layers/models to support various personas – Report consumers, Self‑Service and Advanced SQL Analysts, Data Scientists and AI use cases/agents.
• Create and maintain data domain assets (pipelines/ETLs, semantic models and other assets) using Python, SQL, and other approved tools.
• Build high quality solutions and assets aligned to defined architectural guidelines, data integration patterns, frameworks, and tools.
• Build solutions aligned to security, risk, and compliance guidelines.
• Support analysts and product teams with data products and assigned data domain expertise.
• Assemble large complex data sets that meet functional/non‑functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and re‑designing infrastructure for greater scalability.
• Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.

• Manage business glossary in collaboration with business teams and build/maintain technical metadata for assigned data domains.
• Define data quality rules and controls for assigned data domains and data assets (consumption, gold, silver, bronze layer tables).
• Validate domain datasets for accuracy and completeness. Ensure domain data is of high quality and consumable by reporting, analytics, data science, and AI use cases.

• Collaborate with business leaders, executives, data scientists, BI analytics, product, engineering, and other operational departments to ensure successful delivery of data solutions and data assets (consumption, gold, silver, bronze layer tables).
• Translate business requirements into Data Products and data assets (consumption, gold, silver, bronze layer tables & pipelines) build specifications.

• 8+ years of experience in Data Engineering roles
• 2+ years of warehouse data modeling and pipeline design experience
• Experience with data warehousing:
  Snowflake or similar systems
• Strong Python experience
• Strong SQL experience
• Strong REST API experience
• Experience using Linux.
• Ability and motivation to learn new technologies quickly with minimal support and guidance.
• Strong communication skills
• Experience supporting and working with cross‑functional teams in a dynamic environment.

• AI‑Driven Data Engineering Mindset - Hands‑on experience using AI‑assisted development tools (e.g., Copilot, generative AI) to accelerate pipeline design, code generation, and troubleshooting.
• Intelligent Pipeline Development - Ability to design pipelines that incorporate AI for data transformation, anomaly detection, data classification, and schema evolution.
• AI‑Enabled Data Quality & Observability - Experience using AI/ML techniques for automated data quality checks, root‑cause analysis, and proactive monitoring.
• Metadata & Semantic Layer Enrichment - Ability to use AI to auto‑generate metadata, data documentation, semantic mappings, and business glossary entries

• Full health benefits – Medical/Dental/Vision
• 401(k) match, 6%/3%
• DTO (discretionary time off)
• Health savings account (HSA) with company contribution
• College tuition reimbursement program (STEAM degrees)
• Unlimited use of Linked In Learning
• Free car charging
• Onsite gym and showers

Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.

Upbound is an equal opportunity employer committed to ensuring that all employment decisions are made on a non‑discriminatory basis, and without regard to actual or perceived race.