Data Engineer

Job Description

Responsibilities

• Semantic Modeling Build and maintain Timbr ontologies to unify data across multiple sources.
• BI Integration – Connect Timbr with BI tools (Power BI, Tableau, Looker) for semantic querying and dashboard consistency.
• AI Enablement – Support AI/ML teams with NL2SQL, graph analytics, and ontology-driven agent workflows.
• Governance & Access – Implement Timbr Access Manager for role-based permissions and KPI governance.
• Collaboration – Partner with data engineers, BI analysts, and product owners to ensure semantic consistency across projects.

Mandatory Skills

• Timbr Semantic SQL – Hands-on experience with Timbr’s ontology-based semantic layer.
• SQL & Data Modeling – Strong background in relational databases, semantic SQL, and ontology design.
• BI Tools – Proficiency in Power BI, Tableau, or Looker with semantic integration.
• Graph Analytics – Experience with knowledge graphs, NL2SQL, or AI-driven querying.
• Cloud Platforms – Familiarity with GCP, AWS, or Azure for data pipelines and integration.

Preferred Skills

• AI Agents – Exposure to agentic AI workflows leveraging Timbr ontologies.
• ETL/Data Pipelines – Experience in building scalable pipelines for semantic data integration.
• KPI Governance – Knowledge of enterprise KPI management and semantic consistency.

Qualifications

• Bachelor’s/Master’s in Computer Science, Data Engineering, or related field.
• 5+ years in data engineering, BI, or semantic modeling roles.
• Proven track record of implementing semantic layers in enterprise environments

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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