AI Data Engineer III
Sixt SE (company site, opens in a new tab)9+ yrsBengaluruHybridDirect career pageEst. 30–55 LPA
Posted 2h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and build the semantic layer (metrics, dimensions, entities) on AWS data warehouse as the single source of truth for KPIs consumed by BI tools, analysts, and AI agents.
- Develop and implement text-to-SQL agents covering retrieval, prompt strategy, query generation, validation, and accuracy evaluation pipelines.
- Specify and publish machine-readable ontologies and business glossaries for the mobility domain; integrate semantic context and data lineage into agent workflows and define standards for agent-ready datasets.
Minimum Requirements
- 9+ years of experience in analytics/data engineering, including building semantic or metrics layers and productionizing LLM-based applications such as text-to-SQL or RAG systems.
- Bachelor's or Master's degree in Computer Science or closely related discipline (B.Tech, B.E, or Master's).
- Proficiency in SQL and Python; experience with AWS cloud data warehouses like Redshift, Snowflake, or Databricks; experience with LLM frameworks/APIs (e.g., LangChain, Bedrock, Anthropic API).
- Work Experience Required: 9+ years in relevant domains and technologies.
Ideal Candidate Profile
- Experienced in designing semantic or dimensional data models and familiar with ontology standards (RDF, OWL, SKOS), knowledge graphs, or multi-context platform (MCP) agent context.
- Skilled in engineering best practices including Git, CI/CD, code reviews, testing, with ownership of end-to-end solutions and ability to communicate technical concepts to both technical and business stakeholders.
- Comfortable evaluating emerging semantic layer engines, knowledge graphs, and LLM tooling to drive build-vs-buy decisions in a collaborative team environment.