Sr. Data Engineer – Ontology & Semantic Modeling
SoundThinking
- United States
- United States
Über
Ontology & Semantic Layer
Design, evolve, and maintain ontologies, taxonomies, and semantic models
Define entities and relationships; create mappings from source systems into semantic structures
Establish practical governance practices (versioning, documentation, naming standards)
Ensure semantic consistency across pipelines, APIs, and downstream applications
Data Engineering (Databricks)
Build and operate scalable pipelines using Databricks
Design reliable, well-structured datasets and transformation frameworks
Improve data quality through validation, deduplication, and monitoring
Optimize Spark and SQL workloads for performance and cost efficiency
Database Architecture & Performance (Postgres)
Analyze existing Postgres schemas and query patterns to identify performance bottlenecks
Improve table structures, indexing strategies, and data access patterns
Review query execution plans and optimize joins and filtering logic
Evaluate trade‑offs between normalized, dimensional, and denormalized models
Partner with engineering teams to resolve latency and scaling challenges
AI & Agent Enablement
Structure datasets and metadata to support LLM and agentic AI workflows
Support retrieval use cases (RAG / hybrid search) by preparing clean, linked, high‑signal data
Collaborate with AI teams to validate semantic consistency and correctness
Cloud & Collaboration
Work within AWS environments (S3, IAM, compute, managed databases)
Collaborate across data engineering, AI, product, and platform teams
Document architecture decisions, ontology standards, and best practices
Minimum Qualifications
5+ years in Data Engineering or Data Architecture
Strong experience with Databricks + Spark in production environments
Advanced SQL and strong data modeling skills (conceptual/logical/physical)
Strong experience with Postgres, including schema design and performance tuning
Experience building reliable ETL/ELT pipelines
Proficiency in Python (or Scala) for data engineering workflows
Experience working in AWS environments
Experience implementing data quality practices (validation, deduplication, monitoring)
Nice to Have
Comfortable working with ontology / semantic modeling concepts
Knowledge graph concepts; exposure to RDF/OWL/SPARQL
Graph databases (Neo4j, etc.)
Experience supporting AI/ML or LLM‑based systems (RAG/hybrid retrieval)
Experience with orchestration tools (Airflow, Dagster, dbt)
Experience with governance/lineage tooling (e.g., Unity Catalog)
Travel: 15%
Location: Fremont, CA, Office
Hybrid Workplace Employees are expected to work onsite for a minimum of 3 days per week, unless the advertised role has a specific on‑site requirement.
SoundThinking provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. In addition to federal law requirements, SoundThinking complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
SoundThinking expressly prohibits any form of workplace harassment based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability or veteran status.
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Sprachkenntnisse
- English
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