Pipeline run
e1d7cd36-0c7c-4be5-9ffc-ffd0d21bf053
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the design of data solutions. You will manage the implementing and managing large scale clus…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Streaming / Real-Time Data Engineer
domain · Data Engineering & Analytics CASE DOMAINslug: streaming-real-time-data-engineer · id: 149 · source: db
Domain=Data Engineering & Analytics; The JD centers on building and operating a streaming platform with Kafka, Flink, cluster management, monitoring, and zero-downtime availability, which best matches a streaming/real-time data engineering role.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Introduction At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk. Your Role and Responsibilities As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the design of data solutions. You will manage the implementing and managing large scale cluster for streaming using technologies like kafka, flink, Druid, NoSQL DB etc. Responsibilities Responsible for full operational lifecycle of streaming platform including cluster sizing, technology selection, deployment, monitoring, scaling & helping with kafka apps development Responsible for ensuring platform availability and zero downtime Implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc. If you thrive in a dynamic, collaborative workplace, IBM provides an environment where you will be challenged and inspired every single day. And if you relish the freedom to bring creative, thoughtful solutions to the table, there's no limit to what you can accomplish here. #GBSISACBDS2021 Required Technical and Professional Expertise Minimum 4+ years of experience in Big Data technologies Experience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc Expertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift) Solid practical experience of Cluster Administration and Monitoring using Grafana, Prometheus, ElasticSearch, Kibana or similar technologies Hands on experience on securing clusters - Kerberos, LDAP, TLS, RBAC Demonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers Preferred Technical And Professional Expertise Experience in Python programming is desirable You love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies Ambitious individual who can work under their own direction towards agreed targets/goals and with creative approach to work Intuitive individual with an ability to manage change and proven time management Proven interpersonal skills while contributing to team effort by accomplishing related results as needed Up-to-date technical knowledge by attending educational workshops, reviewing publications NA About Business Unit IBM Services is a team of business, strategy and technology consultants that design, build, and run foundational systems and services that is the backbone of the world's economy. IBM Services partners with the world's leading companies in over 170 countries to build smarter businesses by reimagining and reinventing through technology, with its outcome-focused methodologies, industry-leading portfolio and world class research and operations expertise leading to results-driven innovation and enduring excellence. Your Life @ IBM What matters to you when you’re looking for your next career challenge? Maybe you want to get involved in work that really changes the world? What about somewhere with incredible and diverse career and development opportunities – where you can truly discover your passion? Are you looking for a culture of openness, collaboration and trust – where everyone has a voice? What about all of these? If so, then IBM could be your next career challenge. Join us, not to do something better, but to attempt things you never thought possible. Impact. Inclusion. Infinite Experiences. Do your best work ever. About IBM IBM’s greatest invention is the IBMer. We believe that progress is made through progressive thinking, progressive leadership, progressive policy and progressive action. IBMers believe that the application of intelligence, reason and science can improve business, society and the human condition. Restlessly reinventing since 1911, we are the largest technology and consulting employer in the world, with more than 380,000 IBMers serving clients in 170 countries. Location Statement For additional information about location requirements, please discuss with the recruiter following submission of your application. Being You @ IBM IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Aliases — catalog
- Kafka (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Event Stream Store
- Vendor
- Confluent
- License
- apache_2
- Year introduced
- 2011
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Kafka appears in many production JDs for event streaming and data pipelines, and remains a standard platform in cloud/vendor offerings (e.g., Confluent, AWS MSK), indicating broad hiring demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 3533
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Asynchronous Messaging and Event Streaming Catalog dimension db id 297
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Go Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Scala Backend Developer
-
Messaging and Background Jobs Catalog dimension db id 291
Library dimension (catalog)
Roles linked in library: PHP Backend Developer, Python Backend Developer, Ruby Backend Developer
-
Messaging and Event Streaming Catalog dimension db id 8
Library dimension (catalog)
Roles linked in library: Backend Developer, Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Messaging and Background Jobs
messaging-and-background-jobs
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Apache Flink (CANONICAL) primary
- Apache Flink 1.20 (VERSION)
- Apache Flink 1.x (VERSION)
- Flink 1.20 (VERSION)
- Flink 1.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Stream Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.95
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 1.20
Maturity reasoning: Apache Flink appears in streaming/data-platform JDs, but far less often than Spark/Kafka; GitHub and job-market signals show a specialized real-time processing niche rather than broad hiring staple.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 94
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Stream Processing Systems Catalog dimension db id 25
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Stream Processing Systems
stream-processing-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- NoSQL (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Database Paradigm
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1019
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
NoSQL Databases Catalog dimension db id 19
Library dimension (catalog)
Roles linked in library: Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Apache Spark (CANONICAL)
- apache spark 3 (VERSION)
- spark (VERSION)
- spark 3 (VERSION)
- spark 3.x (VERSION)
- spark3 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Framework
- Sub-category
- Distributed Data Processing Framework
- Vendor
- Apache Software Foundation
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.94
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3.x
Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.
Skill profile (library / DB)
- Skill nature
- FRAMEWORK
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 5
- Sub-category id
- 1021
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
ETL and ELT Tooling Catalog dimension db id 24
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Aliases — catalog
- Docker (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Tool
- Sub-category
- Containerization Tool
- Vendor
- Docker, Inc.
- License
- apache_2
- Year introduced
- 2013
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Docker is a hiring-pipeline staple: it appears in many DevOps, backend, and platform JDs, and remains a standard containerization tool alongside Kubernetes in production stacks.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 13
- Sub-category id
- 63
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Containerization and Image Builds Catalog dimension db id 152
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Deployment and Cloud Platforms Catalog dimension db id 418
Library dimension (catalog)
Roles linked in library: Ruby Backend Developer
-
Deployment and Runtime Configuration Catalog dimension db id 13
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, PHP Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Kubernetes (CANONICAL) primary
- Kubernetes 1.0+ (VERSION)
- Kubernetes 1.x (VERSION)
- Kubernetes v1 (VERSION)
- k8s (VERSION)
- kubernetes 1.x (VERSION)
- kubernetes latest (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Container Orchestration Platform
- Vendor
- Cloud Native Computing Foundation
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.90
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 1.30
Maturity reasoning: Broadly adopted in cloud-native stacks; Kubernetes appears in a large share of DevOps/SRE job descriptions and is the default orchestration platform across major cloud vendors.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 557
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Container Orchestration Platforms Catalog dimension db id 134
Library dimension (catalog)
Roles linked in library: Cloud Architect, DevOps Engineer
-
Kubernetes for ML Workloads Catalog dimension db id 47
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Container Orchestration
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Grafana (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Observability Platform
- Vendor
- Grafana Labs
- License
- apache_2
- Year introduced
- 2014
- Confidence
- 0.90
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Grafana appears in many DevOps/SRE job descriptions and is a standard observability dashboarding tool alongside Prometheus and Loki; strong GitHub/community adoption and broad vendor integrations signal mainstream use.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 176
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Backend Observability, Logging, and Diagnostics Catalog dimension db id 388
Library dimension (catalog)
Roles linked in library: Kotlin Backend Developer, Scala Backend Developer
-
Observability and Incident Response Catalog dimension db id 10
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer
-
Observability and Incident Triage Catalog dimension db id 155
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Observability and Operations Catalog dimension db id 143
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Prometheus (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Platform
- Sub-category
- Monitoring Platform
- Vendor
- Cloud Native Computing Foundation
- License
- apache_2
- Year introduced
- 2012
- Confidence
- 0.62
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Prometheus is widely listed in DevOps/SRE job descriptions and is a standard CNCF monitoring stack component, often paired with Grafana for production observability.
Skill profile (library / DB)
- Skill nature
- PLATFORM
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 9
- Sub-category id
- 2837
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Backend Observability, Logging, and Diagnostics Catalog dimension db id 388
Library dimension (catalog)
Roles linked in library: Kotlin Backend Developer, Scala Backend Developer
-
Observability and Incident Response Catalog dimension db id 10
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer
-
Observability and Incident Triage Catalog dimension db id 155
Library dimension (catalog)
Roles linked in library: DevOps Engineer
-
Observability and Operations Catalog dimension db id 143
Library dimension (catalog)
Roles linked in library: Cloud Architect
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Elasticsearch (CANONICAL) primary
- ES (VERSION)
- ElasticSearch (VERSION)
- Elasticsearch 6 (VERSION)
- Elasticsearch 6.x (VERSION)
- Elasticsearch 7 (VERSION)
- Elasticsearch 7.x (VERSION)
- Elasticsearch 8 (VERSION)
- Elasticsearch 8.x (VERSION)
- Elasticsearch v6 (VERSION)
- Elasticsearch v7 (VERSION)
- Elasticsearch v8 (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Search Datastore
- Vendor
- Elastic NV
- License
- apache_2
- Year introduced
- 2010
- Confidence
- 0.93
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 8.x
Maturity reasoning: Commonly listed in job descriptions for search/log analytics roles and widely deployed in production; Elastic’s docs and ecosystem show sustained adoption rather than sunset or replacement.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 2925
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Magento Search and Indexing Catalog dimension db id 403
Library dimension (catalog)
Roles linked in library: Magento Dev
-
Search and Content Discovery Catalog dimension db id 356
Library dimension (catalog)
Roles linked in library: Drupal Dev, Sitecore Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Magento Search and Indexing
magento-search-and-indexing
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Monitoring Tools
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Security Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- LDAP (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Protocol
- Sub-category
- Directory Access Protocol
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: LDAP remains a common enterprise directory protocol; many JDs still list it for identity, SSO, and directory integration work, especially alongside Active Directory and OpenLDAP.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 10
- Sub-category id
- 2450
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Authentication and Identity Integration Catalog dimension db id 351
Library dimension (catalog)
Roles linked in library: Drupal Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Authentication and Identity Integration
authentication-and-identity-integration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- TLS (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Protocol
- Sub-category
- Transport Security Protocol
- Vendor
- IETF
- License
- other_open
- Year introduced
- 1999
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: TLS is a standard requirement in most security, backend, and cloud job descriptions; it underpins HTTPS and is widely supported by major vendors and browsers, with no announced sunset or replacement.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 10
- Sub-category id
- 1374
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cryptography and PKI Catalog dimension db id 67
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cryptography and PKI
cryptography-and-pki
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- RBAC (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Access Control Concept
- Confidence
- 0.97
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: RBAC is a standard access-control model widely listed in security and IAM job descriptions, and it underpins common products like AWS IAM and Kubernetes RBAC.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 5
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Authentication and Authorization Catalog dimension db id 6
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Go Backend Developer, Java Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer
-
Backend Authentication and Authorization Catalog dimension db id 386
Library dimension (catalog)
Roles linked in library: Kotlin Backend Developer, Ruby Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Authentication and Authorization
authentication-and-authorization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Backend Authentication and Authorization
backend-authentication-and-authorization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Python (CANONICAL) primary
- Python 2 (VERSION)
- Python 2.x (VERSION)
- Python 3 (VERSION)
- Python 3.10 (VERSION)
- Python 3.11 (VERSION)
- Python 3.12 (VERSION)
- Python 3.x (VERSION)
- py (VERSION)
- py2 (VERSION)
- py3 (VERSION)
- python 3 (VERSION)
- python 3.x (VERSION)
- python2 (VERSION)
- python3 (VERSION)
- python3.x (VERSION)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Programming Language
- Vendor
- PSF
- License
- mit
- Year introduced
- 1991
- Confidence
- 0.99
- Version strategy
- SEPARATE_ENTITY
- Version tag
- 3
Maturity reasoning: Python appears in a very high volume of job descriptions across data, backend, automation, and ML roles, and remains a default hiring-pipeline language on major job boards and tech stacks.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 96
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Cloud Security Scripting & DSL Languages Catalog dimension db id 248
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer
-
Programming Languages Catalog dimension db id 1
Library dimension (catalog)
Roles linked in library: Backend Developer, Fullstack Developer
-
Programming Languages and Scripting Catalog dimension db id 59
Library dimension (catalog)
Roles linked in library: Cyber Security Engineer
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
-
Programming Languages for ML Systems Catalog dimension db id 39
Library dimension (catalog)
Roles linked in library: ML Engineer, MLOps Engineer
-
Programming Languages for XR Catalog dimension db id 97
Library dimension (catalog)
Roles linked in library: AR/VR Engineer
-
Python Programming Catalog dimension db id 290
Library dimension (catalog)
Roles linked in library: Python Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Aliases — catalog
- Agile (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Methodology
- Sub-category
- Agile
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.
Skill profile (library / DB)
- Skill nature
- METHODOLOGY
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 8
- Sub-category id
- 367
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
All API 3 persistence rows
Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.
| Skill | Tag | Dimension | Skill↔dim | Role↔dim | Outcome | Notes |
|---|---|---|---|---|---|---|
| Kafka | in_db |
Asynchronous Messaging and Event Streaming
asynchronous-messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kafka | in_db |
Messaging and Background Jobs
messaging-and-background-jobs
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kafka | in_db |
Messaging and Event Streaming
messaging-and-event-streaming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Apache Flink | in_db |
Stream Processing Systems
stream-processing-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| NoSQL | in_db |
NoSQL Databases
nosql-databases
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Apache Spark | in_db |
ETL and ELT Tooling
etl-and-elt-tooling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Containerization and Image Builds
containerization-and-image-builds
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Cloud Platforms
deployment-and-cloud-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Docker | in_db |
Deployment and Runtime Configuration
deployment-and-runtime-configuration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Container Orchestration Platforms
container-orchestration-platforms
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Kubernetes | in_db |
Kubernetes for ML Workloads
kubernetes-for-ml-workloads
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Grafana | in_db |
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Grafana | in_db |
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Grafana | in_db |
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Grafana | in_db |
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Incident Response
observability-and-incident-response
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Incident Triage
observability-and-incident-triage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Prometheus | in_db |
Observability and Operations
observability-and-operations
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Elasticsearch | in_db |
Magento Search and Indexing
magento-search-and-indexing
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Elasticsearch | in_db |
Search and Content Discovery
search-and-content-discovery
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| LDAP | in_db |
Authentication and Identity Integration
authentication-and-identity-integration
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| TLS | in_db |
Cryptography and PKI
cryptography-and-pki
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| RBAC | in_db |
Authentication and Authorization
authentication-and-authorization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| RBAC | in_db |
Backend Authentication and Authorization
backend-authentication-and-authorization
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Cloud Security Scripting & DSL Languages
cloud-security-scripting-dsl-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages
programming-languages
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages and Scripting
programming-languages-and-scripting
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for ML Systems
programming-languages-for-ml-systems
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Programming Languages for XR
programming-languages-for-xr
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Python | in_db |
Python Programming
python-programming
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Agile | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Druid | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Cloud Computing | type=Concepts subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | OpenShift | type=Container Orchestration subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Kibana | type=Monitoring Tools subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Kerberos | type=Security Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "IBM\u2019s greatest invention is the",
"last_5_words": "clients in 170 countries."
},
"text": "IBM\u2019s greatest invention is the IBMer. We believe that progress is made through progressive thinking, progressive leadership, progressive policy and progressive action. IBMers believe that the application of intelligence, reason and science can improve business, society and the human condition. Restlessly reinventing since 1911, we are the largest technology and consulting employer in the world, with more than 380,000 IBMers serving clients in 170 countries.",
"word_count": 64
},
"certifications": [],
"company_name": "IBM",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO",
"Tech Consulting"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 4,
"raw": "Minimum 4+ years of experience in Big Data technologies"
},
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Big Data Engineer",
"Data Platform Engineer",
"Data Solutions Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Your Role and Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "As Data Engineer, you will",
"last_5_words": "Druid, NoSQL DB etc."
},
"text": "As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the design of data solutions. You will manage the implementing and managing large scale cluster for streaming using technologies like kafka, flink, Druid, NoSQL DB etc.",
"word_count": 45
},
{
"bullet_count": 3,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Responsible for full operational lifecycle",
"last_5_words": "big data/cloud technologies Apache Spark"
},
"text": "Responsible for full operational lifecycle of streaming platform including cluster sizing, technology selection, deployment, monitoring, scaling \u0026 helping with kafka apps development.\nResponsible for ensuring platform availability and zero downtime.\nImplement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc.",
"word_count": 54
},
{
"bullet_count": 6,
"heading": "Required Technical and Professional Expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Minimum 4+ years of experience",
"last_5_words": "data mart creation and exposing"
},
"text": "Minimum 4+ years of experience in Big Data technologies.\nExperience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc.\nExpertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift).\nSolid practical experience of Cluster Administration and Monitoring using Grafana, Prometheus, ElasticSearch, Kibana or similar technologies.\nHands on experience on securing clusters - Kerberos, LDAP, TLS, RBAC.\nDemonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers.",
"word_count": 83
},
{
"bullet_count": 6,
"heading": "Preferred Technical And Professional Expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience in Python programming is",
"last_5_words": "attending educational workshops, reviewing"
},
"text": "Experience in Python programming is desirable.\nYou love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies.\nAmbitious individual who can work under their own direction towards agreed targets/goals and with creative approach to work.\nIntuitive individual with an ability to manage change and proven time management.\nProven interpersonal skills while contributing to team effort by accomplishing related results as needed.\nUp-to-date technical knowledge by attending educational workshops, reviewing publications.",
"word_count": 83
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Kafka"
},
{
"is_primary": true,
"skill_name": "Apache Flink"
},
{
"is_primary": true,
"skill_name": "Druid"
},
{
"is_primary": true,
"skill_name": "NoSQL"
},
{
"is_primary": true,
"skill_name": "Apache Spark"
},
{
"is_primary": true,
"skill_name": "Cloud Computing"
},
{
"is_primary": true,
"skill_name": "Docker"
},
{
"is_primary": true,
"skill_name": "Kubernetes"
},
{
"is_primary": false,
"skill_name": "OpenShift"
},
{
"is_primary": true,
"skill_name": "Grafana"
},
{
"is_primary": true,
"skill_name": "Prometheus"
},
{
"is_primary": true,
"skill_name": "Elasticsearch"
},
{
"is_primary": true,
"skill_name": "Kibana"
},
{
"is_primary": true,
"skill_name": "Kerberos"
},
{
"is_primary": true,
"skill_name": "LDAP"
},
{
"is_primary": true,
"skill_name": "TLS"
},
{
"is_primary": true,
"skill_name": "RBAC"
},
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": false,
"skill_name": "Python"
},
{
"is_primary": false,
"skill_name": "Agile"
}
],
"jd_role": {
"display_name": "Data Engineer",
"rationale": null,
"role_aliases": [
"Big Data Engineer",
"Data Platform Engineer",
"Data Solutions Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "IBM\u2019s greatest invention is the",
"last_5_words": "clients in 170 countries."
},
"text": "IBM\u2019s greatest invention is the IBMer. We believe that progress is made through progressive thinking, progressive leadership, progressive policy and progressive action. IBMers believe that the application of intelligence, reason and science can improve business, society and the human condition. Restlessly reinventing since 1911, we are the largest technology and consulting employer in the world, with more than 380,000 IBMers serving clients in 170 countries.",
"word_count": 64
},
"certifications": [],
"company_name": "IBM",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO",
"Tech Consulting"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [],
"experience": {
"max": null,
"min": 4,
"raw": "Minimum 4+ years of experience in Big Data technologies"
},
"job_locations": [],
"role": "Data Engineer",
"role_aliases": [
"Big Data Engineer",
"Data Platform Engineer",
"Data Solutions Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "Your Role and Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "As Data Engineer, you will",
"last_5_words": "Druid, NoSQL DB etc."
},
"text": "As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the design of data solutions. You will manage the implementing and managing large scale cluster for streaming using technologies like kafka, flink, Druid, NoSQL DB etc.",
"word_count": 45
},
{
"bullet_count": 3,
"heading": "Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Responsible for full operational lifecycle",
"last_5_words": "big data/cloud technologies Apache Spark"
},
"text": "Responsible for full operational lifecycle of streaming platform including cluster sizing, technology selection, deployment, monitoring, scaling \u0026 helping with kafka apps development.\nResponsible for ensuring platform availability and zero downtime.\nImplement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc.",
"word_count": 54
},
{
"bullet_count": 6,
"heading": "Required Technical and Professional Expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Minimum 4+ years of experience",
"last_5_words": "data mart creation and exposing"
},
"text": "Minimum 4+ years of experience in Big Data technologies.\nExperience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc.\nExpertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift).\nSolid practical experience of Cluster Administration and Monitoring using Grafana, Prometheus, ElasticSearch, Kibana or similar technologies.\nHands on experience on securing clusters - Kerberos, LDAP, TLS, RBAC.\nDemonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers.",
"word_count": 83
},
{
"bullet_count": 6,
"heading": "Preferred Technical And Professional Expertise",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Experience in Python programming is",
"last_5_words": "attending educational workshops, reviewing"
},
"text": "Experience in Python programming is desirable.\nYou love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies.\nAmbitious individual who can work under their own direction towards agreed targets/goals and with creative approach to work.\nIntuitive individual with an ability to manage change and proven time management.\nProven interpersonal skills while contributing to team effort by accomplishing related results as needed.\nUp-to-date technical knowledge by attending educational workshops, reviewing publications.",
"word_count": 83
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "e1d7cd36-0c7c-4be5-9ffc-ffd0d21bf053",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
"sentence": "Implement scalable solutions to meet the ever-increasing data volumes, using big data/cloud technologies Apache Spark, Kafka, any Cloud computing etc. Minimum 4+ years of experience in Big Data technologies.",
"similarity": 0.6374
},
{
"kra_text": "Develops batch and real-time streaming data pipelines using Apache Spark, Apache Kafka, Apache Flink, or Airflow for data movement and processing at scale.",
"sentence": "You will manage the implementing and managing large scale cluster for streaming using technologies like kafka, flink, Druid, NoSQL DB etc. Responsible for full operational lifecycle of streaming platform including cluster sizing, technology selection, deployment, monitoring, scaling \u0026 helping with kafka apps development.",
"similarity": 0.6371
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Demonstrated ability in solutioning covering data ingestion, data cleansing, ETL, data mart creation and exposing data for consumers.",
"similarity": 0.605
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.6265,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Manages container orchestration with Kubernetes and Docker, deploying applications as pods, managing namespaces, and configuring auto-scaling across cloud environments.",
"sentence": "Experience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc. Expertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift).",
"similarity": 0.5895
},
{
"kra_text": "Responds to deployment failures, infrastructure incidents, and environment misconfiguration issues to restore service availability and prevent recurrence.",
"sentence": "Responsible for ensuring platform availability and zero downtime.",
"similarity": 0.564
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "You love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies.",
"similarity": 0.492
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.5485,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "MLOps Engineer",
"kra_matches": [
{
"kra_text": "Maintains ML platform runbooks, on-call escalation playbooks, and deployment procedure documentation for production operations teams.",
"sentence": "Responsible for ensuring platform availability and zero downtime.",
"similarity": 0.5182
},
{
"kra_text": "Orchestrates model serving deployments to production using Kubernetes, MLflow Model Registry, SageMaker, or Kubeflow Serving infrastructure.",
"sentence": "Experience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc. Expertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift).",
"similarity": 0.4986
},
{
"kra_text": "Orchestrates model serving deployments to production using Kubernetes, MLflow Model Registry, SageMaker, or Kubeflow Serving infrastructure.",
"sentence": "You will manage the implementing and managing large scale cluster for streaming using technologies like kafka, flink, Druid, NoSQL DB etc. Responsible for full operational lifecycle of streaming platform including cluster sizing, technology selection, deployment, monitoring, scaling \u0026 helping with kafka apps development.",
"similarity": 0.4829
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 16,
"score": 0.4999,
"slug": "ml-ops-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "You love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies.",
"similarity": 0.5776
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "You will be involved in the design of data solutions.",
"similarity": 0.433
},
{
"kra_text": "support release readiness",
"sentence": "Responsible for ensuring platform availability and zero downtime.",
"similarity": 0.4262
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.479,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Designs multi-region and multi-availability-zone cloud infrastructure architectures for high availability, fault tolerance, and horizontal scalability.",
"sentence": "Responsible for ensuring platform availability and zero downtime.",
"similarity": 0.4977
},
{
"kra_text": "Designs multi-region and multi-availability-zone cloud infrastructure architectures for high availability, fault tolerance, and horizontal scalability.",
"sentence": "Experience of implementing and managing large scale cluster for streaming kafka, flink, Druid, NoSQL DB etc. Expertise in Contenerizing cluster services using Docker and Kubernetes (preferably using Openshift).",
"similarity": 0.4569
},
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "You love collaborative environments that use agile methodologies to encourage creative design thinking and find innovative ways to develop with cutting edge technologies.",
"similarity": 0.433
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.4625,
"slug": "cloud-architect",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Backend Developer",
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}
API 2 — extract-details
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"input_skill": "Apache Spark",
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"roles_from_db": [
{
"display_name": "Data Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Containerization and Image Builds",
"id": 152,
"rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
"slug": "containerization-and-image-builds",
"source": "db"
},
"input_skill": "Docker",
"llm_role": null,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Cloud Platforms",
"id": 418,
"rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
"slug": "deployment-and-cloud-platforms",
"source": "db"
},
"input_skill": "Docker",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Ruby Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"id": 13,
"rationale": "Configuration and release artifacts that control how backend services run in environments. Includes environment variables, manifests, feature flags, and release-safe configuration management.",
"slug": "deployment-and-runtime-configuration",
"source": "db"
},
"input_skill": "Docker",
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"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"rationale": null,
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},
{
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},
{
"display_name": "Go Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
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{
"display_name": "PHP Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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]
},
{
"dimension": {
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},
"input_skill": "Kubernetes",
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"roles_from_db": [
{
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{
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"role_archetype": null,
"slug": "devops-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Kubernetes for ML Workloads",
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"source": "db"
},
"input_skill": "Kubernetes",
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"roles_from_db": [
{
"display_name": "ML Engineer",
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"role_archetype": null,
"slug": "ml-engineer",
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{
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"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
"slug": "backend-observability-logging-and-diagnostics",
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},
"input_skill": "Grafana",
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"roles_from_db": [
{
"display_name": "Kotlin Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"slug": "observability-and-incident-response",
"source": "db"
},
"input_skill": "Grafana",
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"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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},
{
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"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
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},
{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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"source": "db"
},
{
"display_name": "PHP Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Triage",
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"slug": "observability-and-incident-triage",
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},
"input_skill": "Grafana",
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{
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"role_archetype": null,
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Operations",
"id": 143,
"rationale": "Monitoring, logging, tracing, and operational readiness patterns used to keep cloud platforms supportable. Cloud Architects use this to define what telemetry and operational controls workloads must expose.",
"slug": "observability-and-operations",
"source": "db"
},
"input_skill": "Grafana",
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"roles_from_db": [
{
"display_name": "Cloud Architect",
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"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Backend Observability, Logging, and Diagnostics",
"id": 388,
"rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
"slug": "backend-observability-logging-and-diagnostics",
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},
"input_skill": "Prometheus",
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"roles_from_db": [
{
"display_name": "Kotlin Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
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},
{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Response",
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"slug": "observability-and-incident-response",
"source": "db"
},
"input_skill": "Prometheus",
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"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"role_archetype": "Engineering",
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},
{
"display_name": "Backend Developer",
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"slug": "backend-engineer",
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},
{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Incident Triage",
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"slug": "observability-and-incident-triage",
"source": "db"
},
"input_skill": "Prometheus",
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"roles_from_db": [
{
"display_name": "DevOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Observability and Operations",
"id": 143,
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"source": "db"
},
"input_skill": "Prometheus",
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{
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"role_archetype": null,
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]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"source": "db"
},
"input_skill": "Elasticsearch",
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"roles_from_db": [
{
"display_name": "Magento Dev",
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"rationale": null,
"role_archetype": "Engineering",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Search and Content Discovery",
"id": 356,
"rationale": "Implementing site search, indexing, and content discovery features in Drupal. This cluster is coherent because many Drupal sites need structured search experiences beyond basic navigation.",
"slug": "search-and-content-discovery",
"source": "db"
},
"input_skill": "Elasticsearch",
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"roles_from_db": [
{
"display_name": "Drupal Dev",
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"rationale": null,
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},
{
"display_name": "Sitecore Dev",
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"role_archetype": "Engineering",
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"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Authentication and Identity Integration",
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"rationale": "Sign-in and identity-related integration work for Drupal sites, including external identity providers and session-related behavior. This is distinct from general permissions because it focuses on how users authenticate and federate into the site.",
"slug": "authentication-and-identity-integration",
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},
"input_skill": "LDAP",
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{
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"role_archetype": "Engineering",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Cryptographic primitives and trust infrastructure used to protect data, identities, and communications. This is a coherent cluster because the role needs to reason about keys, certificates, signatures, and protocol internals when reviewing controls.",
"slug": "cryptography-and-pki",
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},
"input_skill": "TLS",
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"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
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"rationale": null,
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},
{
"display_name": "Cyber Security Engineer",
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"role_archetype": null,
"slug": "cybersecurity-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"rationale": "Identity, session, and access-control mechanisms used to protect PHP backend resources. This includes login flows, token handling, role checks, permissions, and policy enforcement in server-side code.",
"slug": "authentication-and-authorization",
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},
"input_skill": "RBAC",
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"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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{
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"slug": "backend-engineer",
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},
{
"display_name": "Go Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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{
"display_name": "Java Backend Developer",
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"rationale": null,
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{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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{
"display_name": "PHP Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Backend Authentication and Authorization",
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"rationale": "Identity and access control mechanisms used by backend services to authenticate users or clients and enforce permissions on protected resources. This includes token and session handling, OAuth 2.0 / OpenID Connect / SAML flows, JWT and access tokens, API keys, MFA, role- or claim-based authorization, RBAC/ABAC, scopes, policies, Spring Security, and authorization filters.",
"slug": "backend-authentication-and-authorization",
"source": "db"
},
"input_skill": "RBAC",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Kotlin Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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{
"display_name": "Ruby Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
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"source": "db"
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{
"display_name": "Scala Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
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"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
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"source": "db"
},
"input_skill": "Python",
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"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
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]
},
{
"dimension": {
"difficulty_hint": "well_known",
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},
"input_skill": "Python",
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"roles_from_db": [
{
"display_name": "Backend Developer",
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{
"display_name": "Fullstack Developer",
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"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
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"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Python",
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"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
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]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
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}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
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"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
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"sub_category_id": 96,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Cloud Security Scripting \u0026 DSL Languages",
"id": 248,
"rationale": "Proficiency in programming and domain-specific languages used to automate and script cloud security controls.",
"slug": "cloud-security-scripting-dsl-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages",
"id": 1,
"rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
"slug": "programming-languages",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages and Scripting",
"id": 59,
"rationale": "Languages used to write security automation, analysis scripts, detection logic, and remediation helpers. This is the primary implementation surface for a cybersecurity engineer across tooling and response workflows.",
"slug": "programming-languages-and-scripting",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for ML Systems",
"id": 39,
"rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
"slug": "programming-languages-for-ml-systems",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for XR",
"id": 97,
"rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
"slug": "programming-languages-for-xr",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AR/VR Engineer",
"id": 8,
"rationale": null,
"role_archetype": null,
"slug": "ar-vr-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"input_skill": "Python",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "Python",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Agile",
"alias_type": "CANONICAL",
"id": 868,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 8,
"display_name": "Agile",
"id": 520,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "METHODOLOGY",
"slug": "agile",
"sub_category_id": 367,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Agile",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Agile",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Druid",
"Cloud Computing",
"OpenShift",
"Kibana",
"Kerberos",
"ETL"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Streaming / Real-Time Data Engineer",
"id": 149,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD centers on building and operating a streaming platform with Kafka, Flink, cluster management, monitoring, and zero-downtime availability, which best matches a streaming/real-time data engineering role.",
"role_archetype": null,
"slug": "streaming-real-time-data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Kafka",
"tag": "in_db"
},
{
"skill": "Apache Flink",
"tag": "in_db"
},
{
"skill": "Druid",
"tag": "new"
},
{
"skill": "NoSQL",
"tag": "in_db"
},
{
"skill": "Apache Spark",
"tag": "in_db"
},
{
"skill": "Cloud Computing",
"tag": "new"
},
{
"skill": "Docker",
"tag": "in_db"
},
{
"skill": "Kubernetes",
"tag": "in_db"
},
{
"skill": "OpenShift",
"tag": "new"
},
{
"skill": "Grafana",
"tag": "in_db"
},
{
"skill": "Prometheus",
"tag": "in_db"
},
{
"skill": "Elasticsearch",
"tag": "in_db"
},
{
"skill": "Kibana",
"tag": "new"
},
{
"skill": "Kerberos",
"tag": "new"
},
{
"skill": "LDAP",
"tag": "in_db"
},
{
"skill": "TLS",
"tag": "in_db"
},
{
"skill": "RBAC",
"tag": "in_db"
},
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "Python",
"tag": "in_db"
},
{
"skill": "Agile",
"tag": "in_db"
}
],
"llm_cost_api1_usd": null,
"llm_cost_api2_usd": null,
"llm_cost_api3_usd": null,
"llm_cost_total_usd": null,
"persistence": {
"items": [
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Asynchronous Messaging and Event Streaming",
"id": 297,
"rationale": "Asynchronous communication patterns and broker technologies used to decouple backend services and move work off the request path. Includes queues, pub/sub, event streams, consumer groups, dead-letter queues, and delivery semantics across systems such as Kafka, RabbitMQ, NATS, SQS/SNS, Pulsar, and ActiveMQ.",
"slug": "asynchronous-messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 297,
"input_skill": "Kafka",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 36,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Background Jobs",
"id": 291,
"rationale": "Asynchronous processing patterns and worker systems used to decouple backend work from request handling. This is a coherent cluster because the role supports background jobs, retries, and deferred processing.",
"slug": "messaging-and-background-jobs",
"source": "db"
},
"dimension_id": 291,
"input_skill": "Kafka",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 36,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Messaging and Event Streaming",
"id": 8,
"rationale": "Transport-layer systems used to move events and decouple producers from consumers. Data engineers use these systems to ingest, buffer, and distribute event data before downstream processing.",
"slug": "messaging-and-event-streaming",
"source": "db"
},
"dimension_id": 8,
"input_skill": "Kafka",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 36,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Stream Processing Systems",
"id": 25,
"rationale": "Technologies for processing event streams and near-real-time data flows. This includes stream transformations, windowing, stateful processing, and stream-to-warehouse delivery patterns.",
"slug": "stream-processing-systems",
"source": "db"
},
"dimension_id": 25,
"input_skill": "Apache Flink",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 120,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "NoSQL Databases",
"id": 19,
"rationale": "Models and manages data using non-relational database systems.",
"slug": "nosql-databases",
"source": "db"
},
"dimension_id": 19,
"input_skill": "NoSQL",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1346,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "ETL and ELT Tooling",
"id": 24,
"rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
"slug": "etl-and-elt-tooling",
"source": "db"
},
"dimension_id": 24,
"input_skill": "Apache Spark",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 1350,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Containerization and Image Builds",
"id": 152,
"rationale": "Container image creation, tagging, hardening, and registry workflows used to package services for deployment. This is coherent because DevOps often owns the build-to-image path that feeds runtime environments.",
"slug": "containerization-and-image-builds",
"source": "db"
},
"dimension_id": 152,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 61,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Cloud Platforms",
"id": 418,
"rationale": "Platform-as-a-Service and container environments for deploying Ruby applications.",
"slug": "deployment-and-cloud-platforms",
"source": "db"
},
"dimension_id": 418,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 61,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Deployment and Runtime Configuration",
"id": 13,
"rationale": "Configuration and release artifacts that control how backend services run in environments. Includes environment variables, manifests, feature flags, and release-safe configuration management.",
"slug": "deployment-and-runtime-configuration",
"source": "db"
},
"dimension_id": 13,
"input_skill": "Docker",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 61,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Container Orchestration Platforms",
"id": 134,
"rationale": "Platforms that schedule and manage containerized workloads across clusters and environments. Cloud Architects need these to define workload placement standards, cluster boundaries, and platform capabilities.",
"slug": "container-orchestration-platforms",
"source": "db"
},
"dimension_id": 134,
"input_skill": "Kubernetes",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Cloud Architect",
"id": 9,
"rationale": null,
"role_archetype": null,
"slug": "cloud-architect",
"source": "db"
},
{
"display_name": "DevOps Engineer",
"id": 10,
"rationale": null,
"role_archetype": null,
"slug": "devops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 726,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Kubernetes for ML Workloads",
"id": 47,
"rationale": "Kubernetes-native components used to schedule, accelerate, and isolate ML training and serving workloads. This includes GPU enablement and ML-specific controllers rather than generic cluster administration.",
"slug": "kubernetes-for-ml-workloads",
"source": "db"
},
"dimension_id": 47,
"input_skill": "Kubernetes",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 726,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Backend Observability, Logging, and Diagnostics",
"id": 388,
"rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
"slug": "backend-observability-logging-and-diagnostics",
"source": "db"
},
"dimension_id": 388,
"input_skill": "Grafana",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
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{
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{
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{
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},
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"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Python Programming",
"id": 290,
"rationale": "Core Python language skills used to implement backend business logic, request handlers, integrations, and service internals. This is the primary coding surface for the role.",
"slug": "python-programming",
"source": "db"
},
"dimension_id": 290,
"input_skill": "Python",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 5,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 149,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"dimension_id": 96,
"input_skill": "Agile",
"llm_role": null,
"matched_chosen_role": false,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
"role_dimension_saved": false,
"roles_from_db": [],
"skill_dimension_saved": true,
"skill_id": 520,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "e1d7cd36-0c7c-4be5-9ffc-ffd0d21bf053"
}
LLM Calls
Every model call made for this run, in pipeline order. Click a card to see the model's response.