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Software Engineer – Semantic Data Team

Job in California, Moniteau County, Missouri, 65018, USA
Listing for: Jobtailor
Full Time position
Listed on 2026-07-20
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Data Engineering, Python, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer – Semantic Data Team
Location: California

  • Design and implement semantically consistent, scalable 360 data models that integrate data across domains
  • Build and maintain transformation pipelines that apply cleansing, standardization, enrichment, and derived logic to domain datasets
  • Write production-quality, testable code in SQL and Python (or equivalent)—delivering performant and maintainable data assets
  • Leverage AI coding assistants (Claude, Copilot, Cursor, and similar) to accelerate development
  • Develop and share patterns, prompts, and workflows that help the team get more leverage out of AI tooling
  • Work closely with domain experts, data scientists, and product stakeholders to translate business concepts into interpretable, decision-ready data models
  • Implement logic for classifications, KPIs, scoring algorithms, and business rules, ensuring traceability and data lineage
  • Help define and enforce standards for data modeling, documentation, and governance within the semantic layer
Requirements
  • 8+ years of experience in data engineering or software engineering with a focus on data transformation, modeling, or analytics platforms
  • Strong proficiency in SQL and at least one general-purpose language such as Python or Scala
  • Demonstrated experience as an AI-native engineer—using tools like Claude, Git Hub Copilot, Cursor, or similar as part of your everyday development workflow
  • Comfort with modern AI engineering practices such as prompt design, context engineering, Spec-Driven Development (SDD)
  • Experience building and scaling wide, entity-based tables and modeling domain concepts (e.g., customer, fleet, provider)
  • Solid understanding of data quality practices—including validation, enrichment, schema enforcement, and business rule encoding
  • Experience working with large-scale datasets and optimizing transformation pipelines for performance and maintainability
  • Comfort operating in a collaborative, cross-functional environment
  • A mindset for traceability, reproducibility, and semantic clarity
  • Bachelor's degree in Computer Science, Software Engineering, or related field
  • A Master's or PhD in Data Science, Machine Learning, Artificial Intelligence, Computer Science, or Statistics is a big plus.
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