Pipeline run
e39a3d07-2be2-4255-ab84-554aac844f6c
Pipeline LLM cost (USD)
API 1: $0.0125
API 2: $0.0000
API 3: $0.0000
Total: $0.0125
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionNature of work
· Cloud Data Engineering / Platform
Own the cloud data platform backlog: prioritize app-team requests, build ingestion/consumption and internal monitoring/testing features, and drive scalable Azure-based infrastructure, CI/CD, and incident handling.
"Developing the framework components for JLL's cloud environment"
Tech stack maturity
Modern Cloud Native
The skill set centers on cloud platforms, serverless, CI/CD, microservices, pub-sub, and modern monitoring/alerting practices, which are characteristic of a modern cloud-native architecture.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 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):
AI
Evidence — skills matched in JD (33)
Python
Node.js
Azure Functions
Cosmos DB
Azure Event Hubs
Azure Data Lake Storage
Azure Storage Queues
AWS
Azure
Microservices
Streaming Technologies
API ingestion
File ingestion
Batch transformation
Metadata management
Pub/Sub
RDBMS
Real-time transformation
Octopus Deploy
Azure DevOps
C#
Azure API Management
Azure Monitor
Azure Table Storage
Azure Databricks
+8
Skill cluster (7 dimension groups, role-scoped)
Cloud Provider Platforms
AWS
Azure
C# and .NET Languages
C#
Cloud Platforms & Managed Services
Azure Functions
JavaScript and TypeScript
Node.js
Observability and Incident Response
Alerting
Python Programming
Python
Cross-cutting / unaligned
Cosmos DB
Azure Event Hubs
Azure Data Lake Storage
Azure Storage Queues
Microservices
Streaming Technologies
API ingestion
File ingestion
Batch transformation
Metadata management
Pub/Sub
RDBMS
Real-time transformation
Octopus Deploy
Azure DevOps
Azure API Management
Azure Monitor
Azure Table Storage
Azure Databricks
Azure SQL Database
Azure AI Search
Azure SignalR
CI/CD
Infrastructure as Code
Agile
Monitoring
Show KRA description ↓
Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.) Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.) Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL's requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL's cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams' needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating "infrastructure as code" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features. Create and maintain incident management requests to product group/engineering group. Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.
Bachelor’s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.
Excellent technical, analytical and organizational skills. Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc.), Micro Services, Streaming Technologies, Network, Security etc., Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation. Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR.
Signals
Skill
backend-engineer
0.24
Alias
data-engineer
1.00
KRA
data-engineer
0.49
Post-classification
Centroidupdated · n=22
Alias collision log—
New-role queue—
New skills captured16
New KRA captured—
Captured for admin review
Azure Event Hubs
primary
↔
Cloud Architect
pending
Azure Data Lake Storage
primary
↔
Cloud Architect
pending
Azure Storage Queues
primary
↔
Cloud Architect
pending
Streaming Technologies
primary
↔
Cloud Architect
pending
API ingestion
primary
↔
Cloud Architect
pending
Batch transformation
primary
↔
Cloud Architect
pending
Real-time transformation
primary
↔
Cloud Architect
pending
Octopus Deploy
primary
↔
Cloud Architect
pending
Azure API Management
primary
↔
Cloud Architect
pending
Azure Monitor
primary
↔
Cloud Architect
pending
Azure Table Storage
primary
↔
Cloud Architect
pending
Azure Databricks
primary
↔
Cloud Architect
pending
Azure SQL Database
primary
↔
Cloud Architect
pending
Azure AI Search
primary
↔
Cloud Architect
pending
Azure SignalR
primary
↔
Cloud Architect
pending
Infrastructure as Code
primary
↔
Cloud Architect
pending
Status:
extract_from_jd_done
Created: 2026-05-27T16:01:34.540788Z
Updated: 2026-05-27T16:01:38.603353Z
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
No chosen role stored for this run.
Job description
Senior Cloud Data Engineer Unified Data Platform JLL/Technologies Centre of Expertise (JLLT CoE) (Bangalore) What this job involves: About The Role #JLLTechAmbitions We are looking for a senior cloud data engineer who is a self-starter to work in a diverse and fast-paced environment to support, maintain and advance the capabilities of the unified data platform.This is an individual contributor role that is responsible for designing, developing and supporting solutions that are strategic for the business and built on the latest technologies and patterns.This a global role that requires partnering with the broader JLLT team at the country, regional and global level by utilizing in-depth knowledge of Azure, infrastructure, technologies and dev/ops engineering experience. Responsibilities Working with the application teams to prioritize new requests for functionality. Specifically, new user-facing functionality (e.g., the ability to ingest IoT data, subscription-based consumption, etc.)Addressing internal functionality (e.g., monitoring and alerting based on application performance, automated testing frameworks, etc.)Managing respective support queues (e.g., Ingest, Prepare, Storage and Consume, etc.) Note: agreed upon SLAs will be established post burn-in periodManage backlog via effective sprint planning based on feedback from the application teamsParticipating in monthly architecture review boardMentoring and coaching the application teams on tools, technology and design patternsEnsuring that the production environment is well built and that there is a clear escalation path for production issuesEnsuring solution architecture meets JLL's requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc.Developing the framework components for JLL's cloud environmentDeveloping infrastructure that is scalable, reliable, and monitoredBuilding a relationship with Cloud providers, in order to take advantage of their most appropriate technology offeringsCollaborating with the application team leads to ensure that the application teams' needs are met through the CI/CD framework, component monitoring and stats, incident escalationInculcating "infrastructure as code" mentality in the Platform \ team overallUtilizing Agile practices to manage and deliver features.Create and maintain incident management requests to product group/engineering group.Compare solution alternatives across both technical and business parameters which support the define cost and service requirements. Sounds like you? To apply you need to be: Experience & Education Bachelor’s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science. Minimum of 3 years of experience as a data and API developer using Python/Nodejs, Azure Functions, Cosmos DB, Azure Event Hubs, Azure Data Lake Storage, Azure Storage Queues etc.Project experience leveraging Agile with SCRUM, and Application Lifecycle Management (ALM). Technical Skills & Competencies Excellent technical, analytical and organizational skills.Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc.), Micro Services, Streaming Technologies, Network, Security etc.,Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR. What we can do for you: You’ll join an entrepreneurial, inclusive culture. One where we succeed together – across the desk and around the globe. Where like-minded people work naturally together to achieve great things. Our Total Rewards program reflects our commitment to helping you achieve your ambitions in career, recognition, well-being, benefits and pay. Join us to develop your strengths and enjoy a fulfilling career full of varied experiences. Keep those ambitions in sights and imagine where JLL can take you... Apply today! JLL Privacy Notice Jones Lang LaSalle (JLL), together with its subsidiaries and affiliates, is a leading global provider of real estate and investment management services. We take our responsibility to protect the personal information provided to us seriously. Generally the personal information we collect from you are for the purposes of processing in connection with JLL’s recruitment process. We endeavour to keep your personal information secure with appropriate level of security and keep for as long as we need it for legitimate business or legal reasons. We will then delete it safely and securely. For more information about how JLL processes your personal data, please view our Candidate Privacy Statement. For additional details please see our career site pages for each country. For employees in the United States, please see a fully copy of our Equal Employment Opportunity and Affirmative Action policy here. Jones Lang LaSalle (“JLL”) is an Equal Opportunity Employer and is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process – including the online application and/or overall selection process – you may email us at AccomodationRequest@am.jll.com. This email is only to request an accommodation. Please direct any other general recruiting inquiries to our Contact Us page > I want to work for JLL.
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Python
Primary
No API 2 row (run stopped after API 1 or history missing)
Node.js
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Functions
Primary
No API 2 row (run stopped after API 1 or history missing)
Cosmos DB
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Event Hubs
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Data Lake Storage
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Storage Queues
Primary
No API 2 row (run stopped after API 1 or history missing)
AWS
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure
Primary
No API 2 row (run stopped after API 1 or history missing)
Microservices
Primary
No API 2 row (run stopped after API 1 or history missing)
Streaming Technologies
Primary
No API 2 row (run stopped after API 1 or history missing)
API ingestion
Primary
No API 2 row (run stopped after API 1 or history missing)
File ingestion
Primary
No API 2 row (run stopped after API 1 or history missing)
Batch transformation
Primary
No API 2 row (run stopped after API 1 or history missing)
Metadata management
Primary
No API 2 row (run stopped after API 1 or history missing)
Pub/Sub
Primary
No API 2 row (run stopped after API 1 or history missing)
RDBMS
Primary
No API 2 row (run stopped after API 1 or history missing)
Real-time transformation
Primary
No API 2 row (run stopped after API 1 or history missing)
Octopus Deploy
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure DevOps
Primary
No API 2 row (run stopped after API 1 or history missing)
C#
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure API Management
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Monitor
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Table Storage
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure Databricks
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure SQL Database
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure AI Search
Primary
No API 2 row (run stopped after API 1 or history missing)
Azure SignalR
Primary
No API 2 row (run stopped after API 1 or history missing)
CI/CD
Primary
No API 2 row (run stopped after API 1 or history missing)
Infrastructure as Code
Primary
No API 2 row (run stopped after API 1 or history missing)
Agile
Primary
No API 2 row (run stopped after API 1 or history missing)
Monitoring
Primary
No API 2 row (run stopped after API 1 or history missing)
Alerting
Primary
No API 2 row (run stopped after API 1 or history missing)
Library artifacts (this run)
No artifact rows for this run.
nano JD Parser — gpt-4.1-nano click to toggle
RoleSenior Cloud Data Engineer
CompanyJones Lang LaSalle (JLL)
ExperienceMinimum of 3-5 years of experience
DomainIT Services & Consulting
Location
Bangalore, India
JD type
pass
Show raw JSON
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"urls": []
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API 1 — extract-from-jd click to toggle
{
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},
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{
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{
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{
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},
{
"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": "Minimum of 3-5 years using the following technology or equivalent: Octopus, Azure DevOps, Azure functions, Python, C#, APIM, Azure Event Hub, Azure Data Lake Storage (Gen 2), Azure Monitor, Azure Table Storage, Azure Databricks, Azure SQL Database, Azure Search, Azure Cosmo Data Store, and Azure SignalR.",
"similarity": 0.4819
},
{
"kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
"sentence": "Specifically, new user-facing functionality (e.g. , the ability to ingest IoT data, subscription-based consumption, etc. ) Addressing internal functionality (e.g. , monitoring and alerting based on application performance, automated testing frameworks, etc. ) Managing respective support queues (e.g. , Ingest, Prepare, Storage and Consume, etc. ) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL\u0027s cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating \"infrastructure as code\" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features.",
"similarity": 0.4645
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.4945,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Specifically, new user-facing functionality (e.g. , the ability to ingest IoT data, subscription-based consumption, etc. ) Addressing internal functionality (e.g. , monitoring and alerting based on application performance, automated testing frameworks, etc. ) Managing respective support queues (e.g. , Ingest, Prepare, Storage and Consume, etc. ) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL\u0027s cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating \"infrastructure as code\" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features.",
"similarity": 0.5302
},
{
"kra_text": "Manages release management processes including environment promotion gates, deployment approval workflows, change management records, and rollback procedures.",
"sentence": "Create and maintain incident management requests to product group/engineering group.",
"similarity": 0.4914
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Working with the application teams to prioritize new requests for functionality.",
"similarity": 0.4607
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.4941,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "Cloud Architect",
"kra_matches": [
{
"kra_text": "Conducts architecture reviews, approves technical design documents, and guides engineering teams through cloud migration and modernization projects.",
"sentence": "Specifically, new user-facing functionality (e.g. , the ability to ingest IoT data, subscription-based consumption, etc. ) Addressing internal functionality (e.g. , monitoring and alerting based on application performance, automated testing frameworks, etc. ) Managing respective support queues (e.g. , Ingest, Prepare, Storage and Consume, etc. ) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL\u0027s cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating \"infrastructure as code\" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features.",
"similarity": 0.5251
},
{
"kra_text": "Evaluates cloud-native managed services, serverless compute, PaaS databases, and CDN solutions for workload fit and total cost of ownership.",
"sentence": "Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.",
"similarity": 0.4945
},
{
"kra_text": "Defines cloud adoption roadmaps, lift-and-shift vs. refactor migration strategies, and landing zone architectures for workloads moving to AWS, Azure, or GCP.",
"sentence": "Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc. ), Micro Services, Streaming Technologies, Network, Security etc. , Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.",
"similarity": 0.4602
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.4933,
"slug": "cloud-architect",
"total_count": null
},
{
"display_name": "Fullstack Developer",
"kra_matches": [
{
"kra_text": "Works closely with product managers and UX designers to translate requirements and wireframes into working software features through iterative development.",
"sentence": "Working with the application teams to prioritize new requests for functionality.",
"similarity": 0.5561
},
{
"kra_text": "Delivers features through CI/CD pipelines using automated tests, staged rollouts, feature flags, and incremental deployments.",
"sentence": "Specifically, new user-facing functionality (e.g. , the ability to ingest IoT data, subscription-based consumption, etc. ) Addressing internal functionality (e.g. , monitoring and alerting based on application performance, automated testing frameworks, etc. ) Managing respective support queues (e.g. , Ingest, Prepare, Storage and Consume, etc. ) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL\u0027s cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating \"infrastructure as code\" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features.",
"similarity": 0.4766
},
{
"kra_text": "Designs and queries relational databases like PostgreSQL and document stores like MongoDB, writing migrations, indexes, and optimized queries.",
"sentence": "Cloud data engineer who is an expert in technology, should be able to quickly adopt to change and one who understands the technologies supporting areas such as Cloud Computing (AWS, Azure, etc. ), Micro Services, Streaming Technologies, Network, Security etc. , Minimum of 3-5 years of experience with, API ingestion, file ingestion, batch transformation, metadata management, monitoring, pub/sub consumption, RDBMS ingestion and real-time transformation.",
"similarity": 0.3816
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.4714,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Engineering Manager",
"kra_matches": [
{
"kra_text": "facilitate technical and delivery decisions",
"sentence": "Compare solution alternatives across both technical and business parameters which support the define cost and service requirements.",
"similarity": 0.4918
},
{
"kra_text": "facilitate technical and delivery decisions",
"sentence": "Specifically, new user-facing functionality (e.g. , the ability to ingest IoT data, subscription-based consumption, etc. ) Addressing internal functionality (e.g. , monitoring and alerting based on application performance, automated testing frameworks, etc. ) Managing respective support queues (e.g. , Ingest, Prepare, Storage and Consume, etc. ) Note: agreed upon SLAs will be established post burn-in period Manage backlog via effective sprint planning based on feedback from the application teams Participating in monthly architecture review board Mentoring and coaching the application teams on tools, technology and design patterns Ensuring that the production environment is well built and that there is a clear escalation path for production issues Ensuring solution architecture meets JLL\u0027s requirements including, but not limited to, those regarding cloud spend, scalability, performance, etc. Developing the framework components for JLL\u0027s cloud environment Developing infrastructure that is scalable, reliable, and monitored Building a relationship with Cloud providers, in order to take advantage of their most appropriate technology offerings Collaborating with the application team leads to ensure that the application teams\u0027 needs are met through the CI/CD framework, component monitoring and stats, incident escalation Inculcating \"infrastructure as code\" mentality in the Platform team overall Utilizing Agile practices to manage and deliver features.",
"similarity": 0.4621
},
{
"kra_text": "Set team goals and delivery plans",
"sentence": "Working with the application teams to prioritize new requests for functionality.",
"similarity": 0.4367
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 121,
"score": 0.4635,
"slug": "engineering-manager",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Backend Developer",
"kra_matches": null,
"matched_count": 8,
"matched_skills": [
"AWS",
"Azure",
"C#",
"Cosmos DB",
"Node.js",
"Python",
"alerting",
"microservices"
],
"role_id": 1,
"score": 0.2424,
"slug": "backend-engineer",
"total_count": 33
},
{
"display_name": "Node.js Backend Developer",
"kra_matches": null,
"matched_count": 7,
"matched_skills": [
"AWS",
"Azure",
"Azure Functions",
"Node.js",
"alerting",
"microservices",
"pub/sub"
],
"role_id": 82,
"score": 0.2121,
"slug": "node-backend-developer",
"total_count": 33
},
{
"display_name": "Fullstack Developer",
"kra_matches": null,
"matched_count": 6,
"matched_skills": [
"AWS",
"Azure",
"Azure Functions",
"C#",
"Node.js",
"Python"
],
"role_id": 15,
"score": 0.1818,
"slug": "full-stack-engineer",
"total_count": 33
},
{
"display_name": "DevOps Engineer",
"kra_matches": null,
"matched_count": 6,
"matched_skills": [
"AWS",
"Azure",
"Azure DevOps",
"CI/CD",
"Monitoring",
"alerting"
],
"role_id": 10,
"score": 0.1818,
"slug": "devops-engineer",
"total_count": 33
},
{
"display_name": ".NET Backend Developer",
"kra_matches": null,
"matched_count": 6,
"matched_skills": [
"AWS",
"Azure",
"Azure Functions",
"C#",
"alerting",
"pub/sub"
],
"role_id": 83,
"score": 0.1818,
"slug": "dotnet-backend-developer",
"total_count": 33
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "Cloud Architect",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 9,
"score": 0.86,
"slug": "cloud-architect",
"total_count": null
},
"confidence": 0.86,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Cloud solution architecture",
"Data ingestion platform engineering",
"Scalable and reliable infrastructure",
"CI/CD and deployment framework design",
"Monitoring and incident management",
"Cloud cost and performance optimization",
"Multi-team technical leadership and mentoring"
],
"matched_kras": [
"Prioritize new requests for functionality",
"Manage backlog via effective sprint planning",
"Participating in monthly architecture review board",
"Ensuring the production environment is well built",
"Developing the framework components for JLL\u0027s cloud environment",
"Developing infrastructure that is scalable, reliable, and monitored",
"Building a relationship with Cloud providers",
"Inculcating \"infrastructure as code\" mentality"
],
"matched_skills": [
"Python",
"Nodejs",
"Azure Functions",
"Cosmos DB",
"Azure Event Hubs",
"Azure Data Lake Storage",
"Azure Storage Queues",
"AWS",
"Azure",
"Micro Services",
"Streaming Technologies",
"CI/CD",
"Infrastructure as code",
"Agile"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Cloud Engineering \u2192 sub-role azure-cloud-architect; The JD is centered on solution/cloud architecture, platform framework design, scalability, CI/CD, and cloud spend/performance tradeoffs rather than a single-provider admin role.",
"sub_role": {
"confidence": 0.97,
"display_name": "Azure Cloud Architect",
"reasoning": "The JD is explicitly centered on Azure services and Azure Functions/Cosmos DB/Event Hubs/Data Lake/Storage Queues, so the Azure-specific architect child fits best.",
"role_id": 101,
"slug": "azure-cloud-architect"
}
},
"stage5_updates": {
"centroid_n_after": 22,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 17828,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Event Hubs",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17829,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Data Lake Storage",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17830,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Storage Queues",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17831,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Streaming Technologies",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17832,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "API ingestion",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17833,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Batch transformation",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17834,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Real-time transformation",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17835,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Octopus Deploy",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17836,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure API Management",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17837,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Monitor",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17838,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Table Storage",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17839,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure Databricks",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17840,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure SQL Database",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17841,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure AI Search",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17842,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Azure SignalR",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 17843,
"role_display_name": "Cloud Architect",
"role_slug": "cloud-architect",
"skill_name": "Infrastructure as Code",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{}
API 3 — final-role-output
{}