Amazon.com Services LLC
Corporate Operations, Ontology, no business category
OntologistII
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Ontologist II at Amazon.com Services LLC. Skills: Ontology, Knowledge Graph, Data pipelines, Generative AI. Build and maintain scalable data pipelines. Perform data cleaning and manipulation”
What You'll Achieve.
Ensure materialized mappings are valid and comprehensive; Ensure high-quality customer experiences; Track improvements; Mitigate customer impact; Improve overall experience; Provide real-time insights; Continuous improvement
Industry & Context.
Troubleshooting; Logic refinement; Debugging tooling issues; Failure space analysis; Root cause analysis; Anomaly detection
Team oncall rotation
What They're Looking For.
Must Have
Bachelor's degree or foreign equivalent, 2 year(s) of progressively responsible experience, 1 year(s) of experience in building and update data models, 1 year(s) experience designing solutions, 1 year(s) experience analyzing and distilling large data sets, 1 year(s) experience working on project ideas with partner teams, 1 year(s) experience interpreting product requirements, 1 year(s) experience presenting solutions, 1 year(s) experience driving operational excellence, 1 year(s) experience pushing code and/or holding design reviews, 1 year(s) experience training new teammates
Nice to Have
PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified certification, dbt Certified certification
What You'll Do.
Build and maintain scalable data pipelines
Perform data cleaning and manipulation
Design and build solutions
Analyze and optimize pipeline performance
Create and maintain documentation
Design and implement ontology structures
Own ontology review documents
Host and participate in ontology discussions
Submit Change Requests (CRs)
Merge CRs in the ontology codebase
Use generative AI tooling to automate processes
Develop mappings using JSON structure
Configure metadata on critical data values
Enable query grounding on Knowledge Graph systems
Create semantic understanding and materialization patterns
Work with partner teams to debug tooling issues
Provide training data for model improvements
Generate billions of quads
Write Cypher queries to add to production index
Record and review Knowledge Graph system projects
Perform pre-launch quality assurance processes
Conduct thorough testing in beta and production environments
Discover and investigate data gaps
Discover and investigate quality issues
Discover and investigate failure patterns
Create detailed reports categorizing issues
Develop measurement frameworks to track improvements
Design and propose actionable solutions
Participate in team oncall rotation
Act as point person for high-severity tickets
Triage issues independently
Triage customer- and internally-reported issues
Perform root cause analysis on non-deterministic systems
Re-assign issues to other teams
Implement short- and long-term resolutions
Design and implement comprehensive monitoring systems
Monitor dashboards for real-time insights
Create automated alerting mechanisms
Establish baseline metrics for continuous improvement
Track Alexa customer utterance defects
Generate aggregated KPI metrics
Write custom SQL logic to create metrics dashboards
How You'll Work.
Team & Collaboration
Partner engineering teams; Partner engineering and science teams; Technical stakeholders; Peer collaboration
Communication Scope
Knowledge sharing; Presenting solutions
Process & Methodology
Change Requests (CRs)
Full Job Description
Employer: Amazon.com Services LLC Position: Ontologist II Location: Santa Barbara, CA Job Number: AMZ20452.4 Multiple Positions Available: 1.Build and maintain scalable data pipelines using extract, transform, and load (ETL) software including Pentaho Data Integration, Amazon Business Data Technologies Cradle, and Amazon Knowledge Graph Data Lake to perfom data cleaning and manipulation on large-scale datasets. Design and build solutions by leveraging off the shelf services like AWS Glue; programming languages including Javascript, SQL, SparkSQL, and Python; custom made tools including Graphiq Imports and Data Lake S3 Crawler; and LLMs (Large Language Models) like Cedric Personas and LLM Batch Inference. Analyze and optimize pipeline performance through systematic monitoring and troubleshooting via query optimization, logic refinement, and tooling collaboration with partner engineering teams. Create and maintain documentation of common ETL resolution procedures for knowledge sharing. 2. Design and implement ontology structures that effectively represent a knowledge domain both conceptually in the real world and based on structured data while maintaining flexibility for future expansion. Own ontology review documents, host and actively participate in ontology discussions, submit Change Requests (CRs), and merge CRs in the ontology codebase. Use generative AI tooling, like Rapid Ontology Creation for KEs (ROCK), to automate ontology and data mapping processes, while integrating expertise at critical decision points. Develop mappings using JSON structure and Jinja templates to establish concrete relationships between data layer and ontological constructs. Configure metadata on critical data values (e.g. foreign keys, external keys, data types) to ensure materialized mappings are valid and comprehensive. 3. Enable query grounding on Amazon Knowledge Graph systems (e.g. Graphiq collections, Knowledge Panels, Neptune Graphs) by creating semantic understanding and material
Applying for this Ontologist II role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about Amazon.com Services LLC?
Real rants from real employees. Read before you apply.