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Pipeline run

bcce2c98-a3d8-4ab3-a284-bc9a1951bb03

Pipeline LLM cost (USD)
API 1: $0.0127 API 2: $0.0005 API 3: $0.0000 Total: $0.0132

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Integration and event handling
Own event-driven, streaming backend systems in production: tune JVMs, containers, and Linux hosts; troubleshoot distributed service issues; and harden designs for security, compliance, and reliable data handling across SQL/NoSQL stacks.
"Extensive coding experience and knowledge in Event driven and streaming architecture"
Tech stack maturity
Mainstream Modern
The skill set centers on widely adopted modern backend practices and platforms like Docker, Kubernetes, CI/CD, event-driven architectures, and JVM-based systems, indicating a mainstream modern stack rather than bleeding-edge or legacy.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3):
Evidence — skills matched in JD (27)
Event-Driven Architecture Streaming Architecture JVM Docker Kubernetes Linux Shell Scripting Design Patterns CI/CD GitHub Jenkins SQL NoSQL Distributed Systems Security Encryption Anonymization Data Integrity CRON ETL JDBC ODBC DNS Proxy ACL +2
Skill cluster (6 dimension groups, role-scoped)
Container Orchestration Platforms
Kubernetes
Deployment and Runtime Configuration
Docker
Java Language and JVM
JVM
NoSQL Databases
NoSQL
Performance and Scalability Tuning
Distributed Systems
Cross-cutting / unaligned
Event-Driven Architecture Streaming Architecture Linux Shell Scripting Design Patterns CI/CD GitHub Jenkins SQL Security Encryption Anonymization Data Integrity CRON ETL JDBC ODBC DNS Proxy ACL Agile Apache Ignite
Show KRA description ↓
• Extensive coding experience and knowledge in Event driven and streaming architecture • Experience in JVM tuning for performance • Knowledge on Containerization using Docker and Kubernetes. • Working knowledge on Caching systems, with particular experience using Apache Ignite will be preferable. [Nice to have] • Linux OS configuration and use, including shell scripting. • Good hands on experience with design patterns and their implementation. • Well versed with CI/CD principles (GitHub, Jenkins etc.), and actively involved in solving, troubleshooting issues in distributed services ecosystem • Experience working with SQL and NoSQL databases • Familiar with Distributed services resiliency and monitoring in a production environment. • Experience in designing, building, testing and implementing security systems – including identifying security design gaps in existing and proposed architectures and recommend changes or enhancements. • Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action. • Knowledge on security controls designing Source and Data Transfers including CRON, ETLs, and JDBC-ODBC scripts. • Understand basics of Networking including DNS, Proxy, ACL, Policy and troubleshooting • High level knowledge of compliance and regulatory requirements of data including but not limited to encryption, anonymization, data integrity, policy control features in large scale infrastructures • Understand data sensitivity in terms of logging, events and in memory data storage– such as no card numbers or personally identifiable data in logs. • Implements wrapper solutions for new/existing components with no/minimal security controls to ensure compliance to bank standards. • Experience in Agile methodology. • Ensure quality of technical and application architecture and design of systems across the organization. • Effectively research and benchmark technology against other best in class technologies. • Experience in Banking, Financial and Fintech experience in an enterprise environment preferred • Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness, by sharing deep knowledge and experience. • Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization. • Have excellent soft and interpersonal skills to interact and present the ideas to team. • The engineer should've good listening skills and speaks clearly in front of team, stakeholders and management. • The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team. • Should be enthusiastic and passionate and creates a motivating environment for the team.

Signals

Skill devops-engineer
0.27
Alias data-engineer
1.00
KRA devops-engineer
0.59

Post-classification

Centroidupdated · n=388
Alias collision log
New-role queue
New skills captured14
New KRA capturedyes

Captured for admin review

Streaming Architecture primary Backend Developer pending
Apache Ignite Backend Developer pending
Linux primary Backend Developer pending
Shell Scripting primary Backend Developer pending
Security primary Backend Developer pending
Encryption primary Backend Developer pending
Anonymization primary Backend Developer pending
Data Integrity primary Backend Developer pending
CRON primary Backend Developer pending
ETL primary Backend Developer pending
JDBC primary Backend Developer pending
ODBC primary Backend Developer pending
Proxy primary Backend Developer pending
ACL primary Backend Developer pending
R&R fragment (sim 0.00) Backend Developer pending

• Extensive coding experience and knowledge in Event driven and streaming architecture • Experience in JVM tuning for performance • Knowledge on Containerization using Docker and Kubernetes. • Working…

Status: completed Created: 2026-05-27T14:13:32.428576Z Updated: 2026-05-27T14:15:48.908923Z API 3 duration: 62610 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Backend Developer

Java Backend Developer

sub-role · 0.94 domain · Software Engineering CASE DOMAIN

slug: backend-engineer · id: 1 · source: db · sub-role slug: java-backend-developer

Domain=Software Engineering → sub-role java-backend-developer; The JD is centered on backend/distributed systems engineering with streaming, containers, databases, CI/CD, Linux, and security controls, which best matches Backend Developer.

Matched skills

Event driven and streaming architectureJVM tuningDockerKubernetesApache IgniteLinux OS configurationshell scriptingCI/CDGitHubJenkinsSQLNoSQLCRONETLsJDBC-ODBCDNSProxyACL

Matched dimensions

Distributed Systems EngineeringPerformance TuningContainerization and OrchestrationDatabase EngineeringCI/CD and Production SupportSecurity Architecture and ComplianceNetworking TroubleshootingTechnical Leadership

Matched KRAs

Work in event driven and streaming architectureTune JVM for performanceContainerization using Docker and KubernetesTroubleshoot issues in distributed services ecosystemDesign and implement security systemsEnsure quality of technical and application architectureDrive compliance with bank standardsInfluence multiple teams on technical considerations

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped

Job description

Job Opportunity with our client in UAE


Job Title :- Data Engineer
location :- Dubai ( remote)
Notice period :- Immediate joiner
Experience :- 5 years


Job Description :-
Education :-
• Degree, Post graduate in Computer Science or related field (or equivalent industry experience)


Experience :-
• Minimum 4+ years of development and design experience in Kafka/Scala with Flink, Beam (or spark streaming) and Kafka


Technical Skills :-
• Extensive coding experience and knowledge in Event driven and streaming architecture
• Experience in JVM tuning for performance
• Knowledge on Containerization using Docker and Kubernetes.
• Working knowledge on Caching systems, with particular experience using Apache Ignite will be preferable. [Nice to have]
• Linux OS configuration and use, including shell scripting.
• Good hands on experience with design patterns and their implementation.
• Well versed with CI/CD principles (GitHub, Jenkins etc.), and actively involved in solving, troubleshooting issues in distributed services ecosystem
• Experience working with SQL and NoSQL databases
• Familiar with Distributed services resiliency and monitoring in a production environment.
• Experience in designing, building, testing and implementing security systems – including identifying security design gaps in existing and proposed architectures and recommend changes or enhancements.
• Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action.
• Knowledge on security controls designing Source and Data Transfers including CRON, ETLs, and JDBC-ODBC scripts.
• Understand basics of Networking including DNS, Proxy, ACL, Policy and troubleshooting
• High level knowledge of compliance and regulatory requirements of data including but not limited to encryption, anonymization, data integrity, policy control features in large scale infrastructures
• Understand data sensitivity in terms of logging, events and in memory data storage– such as no card numbers or personally identifiable data in logs.
• Implements wrapper solutions for new/existing components with no/minimal security controls to ensure compliance to bank standards.


Functional Skills :-
• Experience in Agile methodology.
• Ensure quality of technical and application architecture and design of systems across the organization.
• Effectively research and benchmark technology against other best in class technologies.
• Experience in Banking, Financial and Fintech experience in an enterprise environment preferred
• Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness,
• by sharing deep knowledge and experience.
• Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization


Soft Skills :-
• Have excellent soft and interpersonal skills to interact and present the ideas to team.
• The engineer should've good listening skills and speaks clearly in front of team, stakeholders and management.
• The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team. 
• Should be enthusiastic and passionate and creates a motivating environment for the team.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Event-Driven Architecture Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Event-Driven Architecture id=1360 · event-driven-architecture

Aliases — catalog

  • Event-Driven Architecture (CANONICAL)

Context tags (catalog)

CQRS Kafka RabbitMQ asynchronous messaging data pipeline event bus event schema event sourcing event-driven programming message broker microservices publish-subscribe real-time data serverless stream processing

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Event Driven Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common in cloud-native JDs and vendor docs; AWS, Azure, and Confluent all market event-driven patterns with Kafka/PubSub, showing broad hiring demand.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1027
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)
Streaming Architecture Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Architectural Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
JVM Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: JVM id=1000 · jvm

Aliases — catalog

  • JVM (CANONICAL) primary

Context tags (catalog)

Bytecode Class Loader Cross-Platform Execution Engine Execution Environment Garbage Collection HotSpot JIT Compilation JIT Compiler JVM Options Java Development Kit Java Native Interface Java Runtime Java Runtime Environment Java Virtual Machine Specification Memory Management Performance Tuning Profiling Stack Memory Thread Management

Stored enrichment (catalog DB)

Category
Runtime
Sub-category
Virtual Machine Runtime
Vendor
Oracle
License
other_open
Year introduced
1995
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: JVM is a core runtime in many Java/Kotlin/Scala job descriptions and remains the default execution platform for enterprise backend stacks; major vendors like Oracle and OpenJDK continue active releases, not sunset.

Skill profile (library / DB)

Skill nature
RUNTIME
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
67
Sub-category id
1701
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Java Language and JVM Catalog dimension db id 279

    Library dimension (catalog)

    Roles linked in library: Java Backend Developer, Kotlin Backend Developer, Scala Backend Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Docker Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Docker id=61 · docker

Aliases — catalog

  • Docker (CANONICAL) primary

Context tags (catalog)

CI/CD Compose DevOps Docker Compose Docker Swarm Dockerfile Kubernetes build pipeline container container lifecycle container orchestration container registry container security containerization containers image image registry images immutable infrastructure lightweight virtualization microservices networking orchestration port mapping registry scalability service discovery swarm volume volume management

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 saved
Kubernetes Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Kubernetes id=726 · kubernetes

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)

CI/CD Cluster Autoscaler ConfigMap DaemonSet Deployment Docker Grafana Helm Ingress Istio K8s Kubelet Namespace Pod Prometheus RBAC Secret Service StatefulSet containerization deployment etcd kubectl load balancing microservices namespace orchestration persistent storage scalability service mesh

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)
Apache Ignite Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Databases
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Linux Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Operating Systems
Sub-category
general
Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Shell Scripting Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Programming Languages
Sub-category
general
Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Design Patterns Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: design patterns id=1654 · design-patterns

Aliases — catalog

  • design patterns (CANONICAL)

Context tags (catalog)

Adapter Builder Command Composite Decorator Dependency Injection Facade Factory MVC Observer Prototype SOLID Singleton Strategy Visitor

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Software Design Patterns
Confidence
0.94
Version strategy
NOT_APPLICABLE

Maturity reasoning: Design patterns are a standard interview/JD topic across backend and frontend roles; job postings commonly mention them alongside OOP and system design, and they remain core in books, courses, and code reviews.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1247
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)
CI/CD Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: CI/CD id=1190 · ci-cd

Aliases — catalog

  • CI/CD (CANONICAL)

Context tags (catalog)

Ansible CircleCI Docker GitLab CI Jenkins Kubernetes Terraform Travis CI automated testing build automation continuous deployment continuous integration deployment pipelines monitoring version control

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Ci Cd Process
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: CI/CD appears in a large share of software engineering JDs and is a standard requirement across DevOps, platform, and backend roles; major vendors like GitHub, GitLab, and AWS all center product roadmaps on CI/CD pipelines.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
900
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: GitHub id=280 · github

Aliases — catalog

  • GitHub (CANONICAL) primary

Context tags (catalog)

CI/CD Git GitHub Actions GitHub Enterprise GitHub Pages SSH keys actions branch protection branches code review collaboration commit history fork forking issue tracker issues markdown merge conflicts merge request pull request pull requests release tags repositories repository version control webhooks

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Devops Platform
Vendor
GitHub, Inc.
License
other_open
Year introduced
2008
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: GitHub appears in a very high volume of engineering JDs for source control, code review, and CI/CD; it’s a standard hiring-pipeline skill across teams.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
170
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Jenkins Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Jenkins id=283 · jenkins

Aliases — catalog

  • Jenkins (CANONICAL) primary

Context tags (catalog)

Blue Ocean CI/CD Declarative Pipeline Docker Groovy Jenkinsfile Kubernetes agents artifact repository artifacts automation build triggers integration multibranch pipeline pipeline plugins shared libraries stages test automation version control webhooks

Stored enrichment (catalog DB)

Category
Tool
Sub-category
Ci Cd Tool
Vendor
CloudBees
License
mit
Year introduced
2011
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Jenkins remains a common CI/CD requirement in job postings and enterprise DevOps stacks, with broad plugin ecosystem and long-running GitHub activity despite newer alternatives.

Skill profile (library / DB)

Skill nature
TOOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
13
Sub-category id
184
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • CI/CD Pipeline Platforms Catalog dimension db id 150

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • CI/CD for Machine Learning Catalog dimension db id 56

    Library dimension (catalog)

    Roles linked in library: ML Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: SQL id=101 · sql

Aliases — catalog

  • SQL (CANONICAL) primary

Context tags (catalog)

ACID CTE DDL DML ETL JOIN MySQL NoSQL OLAP ORM PostgreSQL SQL injection SQLite T-SQL data modeling data warehousing database normalization execution plan indexing joins normalization query optimization stored procedures subquery transaction isolation transaction management window functions

Stored enrichment (catalog DB)

Category
Language
Sub-category
Query Language
Vendor
ANSI
License
unknown
Year introduced
1974
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.

Skill profile (library / DB)

Skill nature
LANGUAGE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
6
Sub-category id
97
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Pega Programming Languages & DSLs Catalog dimension db id 267

    Library dimension (catalog)

    Roles linked in library: Pega Developer

  • Programming Languages for Data Work Catalog dimension db id 21

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Pega Programming Languages & DSLs
pega-programming-languages-dsls
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)
NoSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: NoSQL id=1346 · nosql

Aliases — catalog

  • NoSQL (CANONICAL)

Context tags (catalog)

CAP theorem Cassandra DynamoDB MongoDB Redis column-family data modeling document store eventual consistency graph database horizontal scaling key-value store query language schema-less sharding

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 saved
Distributed Systems Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Distributed Systems id=1369 · distributed-systems

Aliases — catalog

  • Distributed Systems (CANONICAL)

Context tags (catalog)

CAP theorem Docker Swarm Kafka MapReduce Zookeeper consensus algorithms distributed databases eventual consistency fault tolerance gRPC load balancing message queues microservices replication sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Distributed Systems
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Common hiring requirement in backend/platform JDs at large tech firms; appears across AWS, Kafka, microservices, and systems roles, with strong GitHub/Stack Overflow activity and no sunset signal.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1035
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Platforms Catalog dimension db id 20

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Cyber Security Engineer, Data Engineer, DevOps Engineer, Fullstack Developer, Go Backend Developer, Java Backend Developer, Kotlin Backend Developer, ML Engineer, MLOps Engineer, Node.js Backend Developer, Python Backend Developer, Scala Backend Developer

  • Performance and Scalability Tuning Catalog dimension db id 11

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension saved
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Security Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Encryption Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Security Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Anonymization Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Privacy
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Integrity Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Quality
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
CRON Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Task Scheduling
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ETL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
JDBC Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Database Connectivity
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ODBC Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Database Connectivity
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
DNS Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: DNS id=740 · dns

Aliases — catalog

  • DNS (CANONICAL) primary

Context tags (catalog)

A record BIND CNAME DNS caching DNS over HTTPS DNS query DNS server DNSSEC MX record NS record PTR record SOA TTL authoritative server dynamic DNS forward lookup forwarding recursive resolver reverse lookup root nameserver split-horizon DNS zone file

Stored enrichment (catalog DB)

Category
Protocol
Sub-category
Name Resolution Protocol
Vendor
IETF
License
other_open
Year introduced
1983
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: DNS is a foundational internet protocol and appears routinely in SRE, network, and cloud job descriptions; major vendors still document and support it as core infrastructure.

Skill profile (library / DB)

Skill nature
PROTOCOL
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
10
Sub-category id
561
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Networking and Connectivity Catalog dimension db id 153

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Cloud Networking and Edge Connectivity Catalog dimension db id 136

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Networking and Connectivity
cloud-networking-and-connectivity
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Cloud Networking and Edge Connectivity
cloud-networking-and-edge-connectivity
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Proxy Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Networking Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ACL Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Security Concepts
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Agile Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

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
Event-Driven Architecture in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JVM in_db
Java Language and JVM
java-language-and-jvm
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JVM in_db
React Frontend Development
d_init_01
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 saved
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)
Design Patterns in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
CI/CD in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GitHub in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Jenkins in_db
CI/CD Pipeline Platforms
ci-cd-pipeline-platforms
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Jenkins in_db
CI/CD for Machine Learning
ci-cd-for-machine-learning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Pega Programming Languages & DSLs
pega-programming-languages-dsls
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL in_db
Programming Languages for Data Work
programming-languages-for-data-work
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension saved
Distributed Systems in_db
Cloud Platforms
cloud-platforms
Existing dimension (library) · Role↔dimension saved
Distributed Systems in_db
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension saved
Distributed Systems in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DNS in_db
Cloud Networking and Connectivity
cloud-networking-and-connectivity
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DNS in_db
Cloud Networking and Edge Connectivity
cloud-networking-and-edge-connectivity
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 Streaming Architecture | type=Architectural Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Apache Ignite | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Linux | type=Operating Systems subtype=general nature=TOOL lifespan=EVERGREEN
canonical_skill_proposed Shell Scripting | type=Programming Languages subtype=general nature=LANGUAGE lifespan=EVERGREEN
canonical_skill_proposed Security | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Encryption | type=Security Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Anonymization | type=Data Privacy subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Data Integrity | type=Data Quality subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed CRON | type=Task Scheduling subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed JDBC | type=Database Connectivity subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ODBC | type=Database Connectivity subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Proxy | type=Networking Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ACL | type=Security Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleData Engineer
ExperienceMinimum 4+ years of development and design experience in Kafka/Scala with Flink, Beam (or spark streaming) and Kafka
DomainIT Services & Consulting
Location Dubai, UAE (remote)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "Tech Consulting",
        "Software Development"
      ],
      "domain": "IT Services \u0026 Consulting"
    },
    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
      "qualification": "Bachelor\u0027s/ Master\u0027s - Computer Science (or related)",
      "raw": "Degree, Post graduate in Computer Science or related field (or equivalent industry experience)",
      "requirement": "required"
    }
  ],
  "experience": {
    "max": null,
    "min": 4,
    "raw": "Minimum 4+ years of development and design experience in Kafka/Scala with Flink, Beam (or spark streaming) and Kafka"
  },
  "job_locations": [
    {
      "aliases": [
        "Dubai, UAE"
      ],
      "city": "Dubai",
      "country": "UAE",
      "state": null,
      "work_mode": "remote"
    }
  ],
  "role": "Data Engineer",
  "role_aliases": [
    "Data Engineer",
    "Software Engineer",
    "Data Developer"
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 15,
      "heading": "Technical Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Extensive coding experience and",
        "last_5_words": "to ensure compliance to bank standards."
      },
      "text": "\u2022 Extensive coding experience and knowledge in Event driven and streaming architecture\n\u2022 Experience in JVM tuning for performance\n\u2022 Knowledge on Containerization using Docker and Kubernetes.\n\u2022 Working knowledge on Caching systems, with particular experience using Apache Ignite will be preferable. [Nice to have]\n\u2022 Linux OS configuration and use, including shell scripting.\n\u2022 Good hands on experience with design patterns and their implementation.\n\u2022 Well versed with CI/CD principles (GitHub, Jenkins etc.), and actively involved in solving, troubleshooting issues in distributed services ecosystem\n\u2022 Experience working with SQL and NoSQL databases\n\u2022 Familiar with Distributed services resiliency and monitoring in a production environment.\n\u2022 Experience in designing, building, testing and implementing security systems \u2013 including identifying security design gaps in existing and proposed architectures and recommend changes or enhancements.\n\u2022 Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action.\n\u2022 Knowledge on security controls designing Source and Data Transfers including CRON, ETLs, and JDBC-ODBC scripts.\n\u2022 Understand basics of Networking including DNS, Proxy, ACL, Policy and troubleshooting\n\u2022 High level knowledge of compliance and regulatory requirements of data including but not limited to encryption, anonymization, data integrity, policy control features in large scale infrastructures\n\u2022 Understand data sensitivity in terms of logging, events and in memory data storage\u2013 such as no card numbers or personally identifiable data in logs.\n\u2022 Implements wrapper solutions for new/existing components with no/minimal security controls to ensure compliance to bank standards.",
      "word_count": 309
    },
    {
      "bullet_count": 6,
      "heading": "Functional Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Experience in Agile methodology.",
        "last_5_words": "across the organization."
      },
      "text": "\u2022 Experience in Agile methodology.\n\u2022 Ensure quality of technical and application architecture and design of systems across the organization.\n\u2022 Effectively research and benchmark technology against other best in class technologies.\n\u2022 Experience in Banking, Financial and Fintech experience in an enterprise environment preferred\n\u2022 Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness,\nby sharing deep knowledge and experience.\n\u2022 Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization.",
      "word_count": 83
    },
    {
      "bullet_count": 4,
      "heading": "Soft Skills",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Have excellent soft and",
        "last_5_words": "for the team."
      },
      "text": "\u2022 Have excellent soft and interpersonal skills to interact and present the ideas to team.\n\u2022 The engineer should\u0027ve good listening skills and speaks clearly in front of team, stakeholders and management.\n\u2022 The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team.\n\u2022 Should be enthusiastic and passionate and creates a motivating environment for the team.",
      "word_count": 66
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Event-Driven Architecture"
    },
    {
      "is_primary": true,
      "skill_name": "Streaming Architecture"
    },
    {
      "is_primary": true,
      "skill_name": "JVM"
    },
    {
      "is_primary": true,
      "skill_name": "Docker"
    },
    {
      "is_primary": true,
      "skill_name": "Kubernetes"
    },
    {
      "is_primary": false,
      "skill_name": "Apache Ignite"
    },
    {
      "is_primary": true,
      "skill_name": "Linux"
    },
    {
      "is_primary": true,
      "skill_name": "Shell Scripting"
    },
    {
      "is_primary": true,
      "skill_name": "Design Patterns"
    },
    {
      "is_primary": true,
      "skill_name": "CI/CD"
    },
    {
      "is_primary": true,
      "skill_name": "GitHub"
    },
    {
      "is_primary": true,
      "skill_name": "Jenkins"
    },
    {
      "is_primary": true,
      "skill_name": "SQL"
    },
    {
      "is_primary": true,
      "skill_name": "NoSQL"
    },
    {
      "is_primary": true,
      "skill_name": "Distributed Systems"
    },
    {
      "is_primary": true,
      "skill_name": "Security"
    },
    {
      "is_primary": true,
      "skill_name": "Encryption"
    },
    {
      "is_primary": true,
      "skill_name": "Anonymization"
    },
    {
      "is_primary": true,
      "skill_name": "Data Integrity"
    },
    {
      "is_primary": true,
      "skill_name": "CRON"
    },
    {
      "is_primary": true,
      "skill_name": "ETL"
    },
    {
      "is_primary": true,
      "skill_name": "JDBC"
    },
    {
      "is_primary": true,
      "skill_name": "ODBC"
    },
    {
      "is_primary": true,
      "skill_name": "DNS"
    },
    {
      "is_primary": true,
      "skill_name": "Proxy"
    },
    {
      "is_primary": true,
      "skill_name": "ACL"
    },
    {
      "is_primary": true,
      "skill_name": "Agile"
    }
  ],
  "jd_role": {
    "display_name": "Data Engineer",
    "rationale": null,
    "role_aliases": [
      "Data Engineer",
      "Software Engineer",
      "Data Developer"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": null,
    "certifications": [],
    "company_name": null,
    "ctc": null,
    "domain": {
      "primary": {
        "aliases": [
          "Tech Consulting",
          "Software Development"
        ],
        "domain": "IT Services \u0026 Consulting"
      },
      "secondary": null
    },
    "education": [
      {
        "level": "Bachelor\u0027s",
        "qualification": "Bachelor\u0027s/ Master\u0027s - Computer Science (or related)",
        "raw": "Degree, Post graduate in Computer Science or related field (or equivalent industry experience)",
        "requirement": "required"
      }
    ],
    "experience": {
      "max": null,
      "min": 4,
      "raw": "Minimum 4+ years of development and design experience in Kafka/Scala with Flink, Beam (or spark streaming) and Kafka"
    },
    "job_locations": [
      {
        "aliases": [
          "Dubai, UAE"
        ],
        "city": "Dubai",
        "country": "UAE",
        "state": null,
        "work_mode": "remote"
      }
    ],
    "role": "Data Engineer",
    "role_aliases": [
      "Data Engineer",
      "Software Engineer",
      "Data Developer"
    ],
    "role_archetype": "Engineering",
    "roles_and_responsibilities": [
      {
        "bullet_count": 15,
        "heading": "Technical Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Extensive coding experience and",
          "last_5_words": "to ensure compliance to bank standards."
        },
        "text": "\u2022 Extensive coding experience and knowledge in Event driven and streaming architecture\n\u2022 Experience in JVM tuning for performance\n\u2022 Knowledge on Containerization using Docker and Kubernetes.\n\u2022 Working knowledge on Caching systems, with particular experience using Apache Ignite will be preferable. [Nice to have]\n\u2022 Linux OS configuration and use, including shell scripting.\n\u2022 Good hands on experience with design patterns and their implementation.\n\u2022 Well versed with CI/CD principles (GitHub, Jenkins etc.), and actively involved in solving, troubleshooting issues in distributed services ecosystem\n\u2022 Experience working with SQL and NoSQL databases\n\u2022 Familiar with Distributed services resiliency and monitoring in a production environment.\n\u2022 Experience in designing, building, testing and implementing security systems \u2013 including identifying security design gaps in existing and proposed architectures and recommend changes or enhancements.\n\u2022 Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action.\n\u2022 Knowledge on security controls designing Source and Data Transfers including CRON, ETLs, and JDBC-ODBC scripts.\n\u2022 Understand basics of Networking including DNS, Proxy, ACL, Policy and troubleshooting\n\u2022 High level knowledge of compliance and regulatory requirements of data including but not limited to encryption, anonymization, data integrity, policy control features in large scale infrastructures\n\u2022 Understand data sensitivity in terms of logging, events and in memory data storage\u2013 such as no card numbers or personally identifiable data in logs.\n\u2022 Implements wrapper solutions for new/existing components with no/minimal security controls to ensure compliance to bank standards.",
        "word_count": 309
      },
      {
        "bullet_count": 6,
        "heading": "Functional Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Experience in Agile methodology.",
          "last_5_words": "across the organization."
        },
        "text": "\u2022 Experience in Agile methodology.\n\u2022 Ensure quality of technical and application architecture and design of systems across the organization.\n\u2022 Effectively research and benchmark technology against other best in class technologies.\n\u2022 Experience in Banking, Financial and Fintech experience in an enterprise environment preferred\n\u2022 Able to influence multiple teams on technical considerations, increasing their productivity and effectiveness,\nby sharing deep knowledge and experience.\n\u2022 Self-motivator and self-starter, Ability to own and drive things without supervision and works collaboratively with the teams across the organization.",
        "word_count": 83
      },
      {
        "bullet_count": 4,
        "heading": "Soft Skills",
        "heading_was_present": true,
        "source_marker": {
          "first_5_words": "\u2022 Have excellent soft and",
          "last_5_words": "for the team."
        },
        "text": "\u2022 Have excellent soft and interpersonal skills to interact and present the ideas to team.\n\u2022 The engineer should\u0027ve good listening skills and speaks clearly in front of team, stakeholders and management.\n\u2022 The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team.\n\u2022 Should be enthusiastic and passionate and creates a motivating environment for the team.",
        "word_count": 66
      }
    ],
    "urls": []
  },
  "rejected": false,
  "rejection_reason": null,
  "run_id": "bcce2c98-a3d8-4ab3-a284-bc9a1951bb03",
  "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": "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": "Knowledge on Containerization using Docker and Kubernetes.",
            "similarity": 0.6357
          },
          {
            "kra_text": "Builds and maintains CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, or CircleCI to automate build, test, security scanning, and deployment workflows.",
            "sentence": "Well versed with CI/CD principles (GitHub, Jenkins etc. ), and actively involved in solving, troubleshooting issues in distributed services ecosystem",
            "similarity": 0.633
          },
          {
            "kra_text": "Responds to deployment failures, infrastructure incidents, and environment misconfiguration issues to restore service availability and prevent recurrence.",
            "sentence": "Responsible for adhering to established policies, following best practices, developing and possessing an in-depth understanding of exploits and vulnerabilities, resolving issues by taking the appropriate corrective action.",
            "similarity": 0.5148
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.5945,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Cyber Security Engineer",
        "kra_matches": [
          {
            "kra_text": "Leads security incident response investigations including forensic analysis, malware triage, containment actions, and post-incident remediation coordination.",
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      {
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      {
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        "display_name": "Backend Developer",
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          "Distributed Systems",
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  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
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    },
    "confidence": 0.93,
    "is_new_role": false,
    "llm2_fired": false,
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    "matched_dimensions": [
      "Distributed Systems Engineering",
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      "Containerization and Orchestration",
      "Database Engineering",
      "CI/CD and Production Support",
      "Security Architecture and Compliance",
      "Networking Troubleshooting",
      "Technical Leadership"
    ],
    "matched_kras": [
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      "Containerization using Docker and Kubernetes",
      "Troubleshoot issues in distributed services ecosystem",
      "Design and implement security systems",
      "Ensure quality of technical and application architecture",
      "Drive compliance with bank standards",
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    "matched_skills": [
      "Event driven and streaming architecture",
      "JVM tuning",
      "Docker",
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      "Apache Ignite",
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      },
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}
API 2 — extract-details
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      "alias_persisted": false,
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      "existing_alias_text": "Docker",
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
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      "matched_via": "alias"
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      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
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      "matched_via": "alias"
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      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Streaming Architecture",
    "Apache Ignite",
    "Linux",
    "Shell Scripting",
    "Security",
    "Encryption",
    "Anonymization",
    "Data Integrity",
    "CRON",
    "ETL",
    "JDBC",
    "ODBC",
    "Proxy",
    "ACL"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Backend Developer",
    "id": 1,
    "rationale": "Domain=Software Engineering \u2192 sub-role java-backend-developer; The JD is centered on backend/distributed systems engineering with streaming, containers, databases, CI/CD, Linux, and security controls, which best matches Backend Developer.",
    "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"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Event-Driven Architecture",
      "tag": "in_db"
    },
    {
      "skill": "Streaming Architecture",
      "tag": "new"
    },
    {
      "skill": "JVM",
      "tag": "in_db"
    },
    {
      "skill": "Docker",
      "tag": "in_db"
    },
    {
      "skill": "Kubernetes",
      "tag": "in_db"
    },
    {
      "skill": "Apache Ignite",
      "tag": "new"
    },
    {
      "skill": "Linux",
      "tag": "new"
    },
    {
      "skill": "Shell Scripting",
      "tag": "new"
    },
    {
      "skill": "Design Patterns",
      "tag": "in_db"
    },
    {
      "skill": "CI/CD",
      "tag": "in_db"
    },
    {
      "skill": "GitHub",
      "tag": "in_db"
    },
    {
      "skill": "Jenkins",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "Distributed Systems",
      "tag": "in_db"
    },
    {
      "skill": "Security",
      "tag": "new"
    },
    {
      "skill": "Encryption",
      "tag": "new"
    },
    {
      "skill": "Anonymization",
      "tag": "new"
    },
    {
      "skill": "Data Integrity",
      "tag": "new"
    },
    {
      "skill": "CRON",
      "tag": "new"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "JDBC",
      "tag": "new"
    },
    {
      "skill": "ODBC",
      "tag": "new"
    },
    {
      "skill": "DNS",
      "tag": "in_db"
    },
    {
      "skill": "Proxy",
      "tag": "new"
    },
    {
      "skill": "ACL",
      "tag": "new"
    },
    {
      "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": 1,
        "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": "Event-Driven Architecture",
        "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": 1360,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Java Language and JVM",
          "id": 279,
          "rationale": "Core Java implementation skills used to build backend service logic, utilities, and internal abstractions. This is the primary coding surface for the role and includes language features plus JVM behavior that affect correctness and maintainability.",
          "slug": "java-language-and-jvm",
          "source": "db"
        },
        "dimension_id": 279,
        "input_skill": "JVM",
        "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": "Java Backend Developer",
            "id": 79,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "java-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": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1000,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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": "JVM",
        "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": 1000,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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": 1,
        "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": 1,
        "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": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "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": 1,
        "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": 1,
        "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": 1,
        "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": "Design Patterns",
        "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": 1654,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "CI/CD",
        "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": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "CI/CD",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1190,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "GitHub",
        "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": 280,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "GitHub",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 280,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD Pipeline Platforms",
          "id": 150,
          "rationale": "Systems used to define, run, and maintain automated build and deployment workflows. This cluster is coherent because the role owns delivery automation end to end, including pipeline reliability and promotion logic.",
          "slug": "ci-cd-pipeline-platforms",
          "source": "db"
        },
        "dimension_id": 150,
        "input_skill": "Jenkins",
        "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": 283,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "CI/CD for Machine Learning",
          "id": 56,
          "rationale": "Tools and platforms for automating ML model integration, testing, and deployment pipelines.",
          "slug": "ci-cd-for-machine-learning",
          "source": "db"
        },
        "dimension_id": 56,
        "input_skill": "Jenkins",
        "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 283,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Pega Programming Languages \u0026 DSLs",
          "id": 267,
          "rationale": "Programming languages and domain-specific languages used in Pega development.",
          "slug": "pega-programming-languages-dsls",
          "source": "db"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "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": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
        "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": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 1,
        "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": true,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
        "role_dimension_saved": true,
        "roles_from_db": [
          {
            "display_name": "Backend Developer",
            "id": 1,
            "rationale": null,
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}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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