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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro role with common Data Engineer demand and some niche LLM specialization.
Requires deep semantic modeling, data platform, and LLM experience, limiting cross-industry transferability.
Explicit 9+ years and mandatory semantic, cloud, SQL, Python, and LLM production experience.
Job Description
Structured overview of role & requirementsAbout This Role
Design and build the semantic layer (metrics, dimensions, entities) on an AWS data warehouse to serve BI tools, analysts, and AI agents as a single source of truth for KPIs.
Develop and productionize text-to-SQL agents including retrieval, prompt strategies, query generation, validation, and accuracy evaluation pipelines.
Specify and publish ontologies and business glossaries for the mobility domain for consumption by agents and services; integrate semantic context and metadata to enable agent-ready datasets.
Minimum Requirements
9+ years of experience in analytics/data engineering with hands-on experience in semantic or metrics layer construction and LLM-based application productionization.
Proficiency in SQL and Python; experience with AWS cloud data warehouses like Redshift, Snowflake, or Databricks and LLM frameworks/APIs (e.g., LangChain, Bedrock, Anthropic API).
Bachelor's or Master's degree in Computer Science or related discipline (B.Tech, B.E., or Master's) required.
Experience with dimensional and semantic data modeling or ontology standards is highly preferred but not explicitly mandatory.
Ideal Candidate Profile
Demonstrates expertise in semantic modeling and metrics layer technologies with practical LLM-driven application experience, especially text-to-SQL or retrieval-augmented generation systems.
Able to work end-to-end including engineering best practices and clearly communicate complex concepts to technical and business stakeholders.
Experienced in collaborating with cross-functional teams (data engineers, analysts, AI platform teams) and driving tooling and integration decisions in a cloud-based data environment.