Pipeline run
8fbfdf67-0873-427e-aeef-1556f3bedbcf
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionvocab breakdown (legacy)
Signals
Post-classification
Captured for admin review
As a part of the AI, Martech, and Personalization team, youll act as a bridge between marketing, data, and development teams. Youll play a part in our mission to drive data-powered marketing by enabli…
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Business Analyst (Tech)
domain · Tech-Adjacent CASE DOMAINslug: business-analyst-tech · id: 114 · source: db
Domain=Tech-Adjacent; The role is centered on translating personalization and segmentation business needs into technical specs, user stories, documentation, and cross-functional coordination, which best matches a technical business analyst.
Matched skills
Matched dimensions
Matched KRAs
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
When you join Verizon You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife. What Youll Be Doing As a part of the AI, Martech, and Personalization team, youll act as a bridge between marketing, data, and development teams. Youll play a part in our mission to drive data-powered marketing by enabling segmentation, automation, and dynamic personalization. This is your chance to be a vital part of an innovative, fast-moving team where your ideas and technical expertise drive success. The Martech & Personalization Specialist works to connect platform capabilities and data to marketing use cases. As a data-driven team member, youll work closely with data, development, analytics, AI, marketing, and other partners to build, implement, and maintain solutions to support personalized journeys and experiences. Youll be working on identity resolution, real-time events, and data flows, working with cross-functional teams to ensure real-time behaviors and data needed to power campaigns is available and high-quality. Youll have an in-depth functional understanding of customer data platforms (CDPs) and marketing automation platforms and a strong understanding of digital marketing. Additionally, youll be working hands-on to configure the platforms, support complex campaigns, and enable new functionality. As Martech & Personalization Specialist, youll be expected to create technical documentation, translate business needs into technical user stories for development, and manage and assist with UAT. Youll also be expected to enter and manage trouble tickets, and assist with monitoring data flows. The ideal candidate is proficient in technical problem-solving but also has a business-oriented vision. You understand how operational roles solve everyday business needs. Responsibilities Include • Working with internal teams to understand business requirements for personalization and segmentation use cases, then translating them into technical specification documentation and writing technical user stories for development teams. • Collaborating closely with cross-functional teams, including Analytics, AI&D, Business Intelligence, and Enterprise Architecture, to identify and document data requirements and implement effective and compliant data collection strategies like tagging, streaming, or batch delivery. • Documenting architecture, data flows, processes, and configurations across the tech stack. Maintaining a data dictionary for marketing automation platform and CDP. • Assisting with CDP and marketing automation platform configuration to capture, integrate, manage, and activate customer data for marketing campaigns. • Participating in User Acceptance Testing (UAT) for personalization use cases and other activities. • Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery. • Entering and managing trouble tickets for platform performance or data collection issues across the entire stack with internal and external support teams. • Monitoring and optimizing platform performance. • Communicating project status, timelines, deliverables, and roadblocks to partners and team members. • Testing and enabling AI and Machine Learning features, built by internal teams or embedded within the platforms, to evolve platform capabilities. • Partnering with internal SMEs to create, document, and maintain data governance practices, ensuring data quality, integrity, and compliance with privacy regulations (e.g., GDPR, CCPA). • Contributing to standards and best practices, fostering consistency and efficiency. • Providing training and support to internal stakeholders. • Providing recommendations for business process redesign and best practices; creating documentation as needed. • Establishing strong relationships with internal stakeholders and partners. • Staying up to date with industry trends, best practices, and emerging technologies related to customer data management and personalization. Youll Need To Have • Bachelors degree in digital marketing, marketing, or a related field. • 2 or more years of relevant work experience. • Hands-on experience working with customer data platforms (like Adobe Experience Platform), marketing automation platforms (like Marketo or Eloqua), or sales CRMs. • 2 or more years experience with digital marketing. • 2 or more years experience partnering with IT and/or marketing to deliver technology-based, data-driven use cases. • Significant experience leveraging front-end technologies such as Javascript in the context of marketing technology platforms. • Ability to meet deadlines, manage multiple projects simultaneously, and work in a fast-paced, dynamic, customer and team-oriented work environment. • Strong problem-solving skills and the ability to make data-driven decisions. • Great communication skills; you can translate business needs to technical teams and vice versa. Even better if you have: • Experience with data architecture and customer data modeling. • Adobe Real Time CDP Developer Expert Certification or Adobe Real Time CDP Business Practitioner Professional Certification. • Marketo Expert Certification. • Experience with Adobe Experience Platform B2B RTCDP, Marketo Engage, Adobe Journey Optimizer, Adobe Target, and Adobe Launch. • Extensive experience working with APIs (REST, webhooks, SOAP, etc.). • Significant experience working with large datasets and working with query languages such as SQL. • Understanding of SDK implementations. If Verizon and this role sound like a fit for you, we encourage you to apply even if you dont meet every even better qualification listed above. #VBGDXP Where youll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Equal Employment Opportunity Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics. Locations • Hyderabad, India • Chennai, India
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Cloud Platforms
- Sub-category
- general
- Skill nature
- PLATFORM
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Practices
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- AI (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Artificial Intelligence
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: AI appears in a large and growing share of job descriptions across software, data, and product roles; major vendors like Microsoft, Google, and AWS have broad AI offerings and hiring demand reflects mainstream adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1020
- 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) |
Aliases — catalog
- Machine Learning (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Machine Learning
- Confidence
- 0.98
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 1024
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
AI Governance and Model Security Catalog dimension db id 50
Library dimension (catalog)
Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer
-
React Frontend Development Catalog dimension db id 96
Library dimension (catalog)
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Concepts
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- GDPR (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Standard
- Sub-category
- Privacy Regulation Standard
- Vendor
- European Union
- Year introduced
- 2016
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: GDPR is a widely cited compliance requirement in job postings for product, legal, security, and data roles across EU-facing companies; it remains an active regulatory standard rather than a niche tool.
Skill profile (library / DB)
- Skill nature
- STANDARD
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 12
- Sub-category id
- 3215
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Compliance and Security Frameworks Catalog dimension db id 73
Library dimension (catalog)
Roles linked in library: Cloud Security Engineer, Cyber Security Engineer
-
Standards, Protocols & Compliance Catalog dimension db id 452
Library dimension (catalog)
Roles linked in library: Engineering Manager, Sitecore Dev
-
Web Standards & Compliance Catalog dimension db id 343
Library dimension (catalog)
Roles linked in library: WordPress Dev
-
Web Standards, Protocols & Compliance Catalog dimension db id 436
Library dimension (catalog)
Roles linked in library: Shopify Dev
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Compliance and Security Frameworks
compliance-and-security-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Standards & Compliance
web-standards-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Web Standards, Protocols & Compliance
web-standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Credentials
- Sub-category
- general
- Skill nature
- CREDENTIAL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
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 |
|---|---|---|---|---|---|---|
| AI | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
AI Governance and Model Security
ai-governance-and-model-security
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Machine Learning | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GDPR | in_db |
Compliance and Security Frameworks
compliance-and-security-frameworks
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GDPR | in_db |
Standards, Protocols & Compliance
standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GDPR | in_db |
Web Standards & Compliance
web-standards-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| GDPR | in_db |
Web Standards, Protocols & Compliance
web-standards-protocols-compliance
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Customer Data Platforms | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Marketing Automation Platforms | type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Identity Resolution | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Real-time Events | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Flows | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Segmentation | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Automation | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Dynamic Personalization | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Tagging | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Streaming | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Batch Delivery | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | User Acceptance Testing | type=Practices subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Governance | type=Concepts subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | CCPA | type=Credentials subtype=general nature=CREDENTIAL lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
Certifications
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "You want more out of",
"last_5_words": "join the #VTeamLife."
},
"text": "You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere \u0026 always. Want in? Join the #VTeamLife.",
"word_count": 100
},
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"data platforms",
"webhooks",
"Make",
"Monitoring",
"APIs",
"Analytics",
"Machine Learning",
"Role",
"SOAP",
"REST",
"JavaScript",
"Location",
"SQL",
"relationships",
"roles",
"GDPR",
"use cases"
],
"certifications": [
"Adobe Real Time CDP Developer Expert Certification",
"Adobe Real Time CDP Business Practitioner Professional Certification",
"Marketo Expert Certification"
],
"company_name": "Verizon",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Tech Consulting",
"Marketing Technology"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/BSC - Digital Marketing (or related)",
"raw": "Bachelors degree in digital marketing, marketing, or a related field.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 2,
"raw": "2 or more years of relevant work experience"
},
"job_locations": [
{
"aliases": [
"Hyderabad, IN"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": "hybrid"
},
{
"aliases": [
"Chennai, IN"
],
"city": "Chennai",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Martech \u0026 Personalization Specialist",
"role_aliases": [
"Marketing Technology Specialist",
"Personalization Specialist",
"Martech Specialist"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "What Youll Be Doing",
"heading_was_present": true,
"source_marker": {
"first_5_words": "As a part of the AI,",
"last_5_words": "support complex campaigns, and enable"
},
"text": "As a part of the AI, Martech, and Personalization team, youll act as a bridge between marketing, data, and development teams. Youll play a part in our mission to drive data-powered marketing by enabling segmentation, automation, and dynamic personalization. This is your chance to be a vital part of an innovative, fast-moving team where your ideas and technical expertise drive success.\n\nThe Martech \u0026 Personalization Specialist works to connect platform capabilities and data to marketing use cases. As a data-driven team member, youll work closely with data, development, analytics, AI, marketing, and other partners to build, implement, and maintain solutions to support personalized journeys and experiences.\n\nYoull be working on identity resolution, real-time events, and data flows, working with cross-functional teams to ensure real-time behaviors and data needed to power campaigns is available and high-quality. Youll have an in-depth functional understanding of customer data platforms (CDPs) and marketing automation platforms and a strong understanding of digital marketing. Additionally, youll be working hands-on to configure the platforms, support complex campaigns, and enable new functionality.",
"word_count": 218
},
{
"bullet_count": 15,
"heading": "Responsibilities Include",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Working with internal teams",
"last_5_words": "data management and personalization."
},
"text": "\u2022 Working with internal teams to understand business requirements for personalization and segmentation use cases, then translating them into technical specification documentation and writing technical user stories for development teams.\n\u2022 Collaborating closely with cross-functional teams, including Analytics, AI\u0026D, Business Intelligence, and Enterprise Architecture, to identify and document data requirements and implement effective and compliant data collection strategies like tagging, streaming, or batch delivery.\n\u2022 Documenting architecture, data flows, processes, and configurations across the tech stack. Maintaining a data dictionary for marketing automation platform and CDP.\n\u2022 Assisting with CDP and marketing automation platform configuration to capture, integrate, manage, and activate customer data for marketing campaigns.\n\u2022 Participating in User Acceptance Testing (UAT) for personalization use cases and other activities.\n\u2022 Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery.\n\u2022 Entering and managing trouble tickets for platform performance or data collection issues across the entire stack with internal and external support teams.\n\u2022 Monitoring and optimizing platform performance.\n\u2022 Communicating project status, timelines, deliverables, and roadblocks to partners and team members.\n\u2022 Testing and enabling AI and Machine Learning features, built by internal teams or embedded within the platforms, to evolve platform capabilities.\n\u2022 Partnering with internal SMEs to create, document, and maintain data governance practices, ensuring data quality, integrity, and compliance with privacy regulations (e.g., GDPR, CCPA).\n\u2022 Contributing to standards and best practices, fostering consistency and efficiency.\n\u2022 Providing training and support to internal stakeholders.\n\u2022 Providing recommendations for business process redesign and best practices; creating documentation as needed.\n\u2022 Establishing strong relationships with internal stakeholders and partners.\n\u2022 Staying up to date with industry trends, best practices, and emerging technologies related to customer data management and personalization.",
"word_count": 335
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "Customer Data Platforms"
},
{
"is_primary": true,
"skill_name": "Marketing Automation Platforms"
},
{
"is_primary": true,
"skill_name": "Identity Resolution"
},
{
"is_primary": true,
"skill_name": "Real-time Events"
},
{
"is_primary": true,
"skill_name": "Data Flows"
},
{
"is_primary": true,
"skill_name": "Segmentation"
},
{
"is_primary": true,
"skill_name": "Automation"
},
{
"is_primary": true,
"skill_name": "Dynamic Personalization"
},
{
"is_primary": true,
"skill_name": "Tagging"
},
{
"is_primary": true,
"skill_name": "Streaming"
},
{
"is_primary": true,
"skill_name": "Batch Delivery"
},
{
"is_primary": true,
"skill_name": "User Acceptance Testing"
},
{
"is_primary": true,
"skill_name": "AI"
},
{
"is_primary": true,
"skill_name": "Machine Learning"
},
{
"is_primary": true,
"skill_name": "Data Governance"
},
{
"is_primary": true,
"skill_name": "GDPR"
},
{
"is_primary": true,
"skill_name": "CCPA"
}
],
"jd_role": {
"display_name": "Martech \u0026 Personalization Specialist",
"rationale": null,
"role_aliases": [
"Marketing Technology Specialist",
"Personalization Specialist",
"Martech Specialist"
],
"role_archetype": "Engineering",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "You want more out of",
"last_5_words": "join the #VTeamLife."
},
"text": "You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere \u0026 always. Want in? Join the #VTeamLife.",
"word_count": 100
},
"archetype_override_applied": true,
"archetype_override_matched_skills": [
"data platforms",
"webhooks",
"Make",
"Monitoring",
"APIs",
"Analytics",
"Machine Learning",
"Role",
"SOAP",
"REST",
"JavaScript",
"Location",
"SQL",
"relationships",
"roles",
"GDPR",
"use cases"
],
"certifications": [
"Adobe Real Time CDP Developer Expert Certification",
"Adobe Real Time CDP Business Practitioner Professional Certification",
"Marketo Expert Certification"
],
"company_name": "Verizon",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Tech Consulting",
"Marketing Technology"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE/BSC - Digital Marketing (or related)",
"raw": "Bachelors degree in digital marketing, marketing, or a related field.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 2,
"raw": "2 or more years of relevant work experience"
},
"job_locations": [
{
"aliases": [
"Hyderabad, IN"
],
"city": "Hyderabad",
"country": "India",
"state": null,
"work_mode": "hybrid"
},
{
"aliases": [
"Chennai, IN"
],
"city": "Chennai",
"country": "India",
"state": null,
"work_mode": "hybrid"
}
],
"role": "Martech \u0026 Personalization Specialist",
"role_aliases": [
"Marketing Technology Specialist",
"Personalization Specialist",
"Martech Specialist"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "What Youll Be Doing",
"heading_was_present": true,
"source_marker": {
"first_5_words": "As a part of the AI,",
"last_5_words": "support complex campaigns, and enable"
},
"text": "As a part of the AI, Martech, and Personalization team, youll act as a bridge between marketing, data, and development teams. Youll play a part in our mission to drive data-powered marketing by enabling segmentation, automation, and dynamic personalization. This is your chance to be a vital part of an innovative, fast-moving team where your ideas and technical expertise drive success.\n\nThe Martech \u0026 Personalization Specialist works to connect platform capabilities and data to marketing use cases. As a data-driven team member, youll work closely with data, development, analytics, AI, marketing, and other partners to build, implement, and maintain solutions to support personalized journeys and experiences.\n\nYoull be working on identity resolution, real-time events, and data flows, working with cross-functional teams to ensure real-time behaviors and data needed to power campaigns is available and high-quality. Youll have an in-depth functional understanding of customer data platforms (CDPs) and marketing automation platforms and a strong understanding of digital marketing. Additionally, youll be working hands-on to configure the platforms, support complex campaigns, and enable new functionality.",
"word_count": 218
},
{
"bullet_count": 15,
"heading": "Responsibilities Include",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Working with internal teams",
"last_5_words": "data management and personalization."
},
"text": "\u2022 Working with internal teams to understand business requirements for personalization and segmentation use cases, then translating them into technical specification documentation and writing technical user stories for development teams.\n\u2022 Collaborating closely with cross-functional teams, including Analytics, AI\u0026D, Business Intelligence, and Enterprise Architecture, to identify and document data requirements and implement effective and compliant data collection strategies like tagging, streaming, or batch delivery.\n\u2022 Documenting architecture, data flows, processes, and configurations across the tech stack. Maintaining a data dictionary for marketing automation platform and CDP.\n\u2022 Assisting with CDP and marketing automation platform configuration to capture, integrate, manage, and activate customer data for marketing campaigns.\n\u2022 Participating in User Acceptance Testing (UAT) for personalization use cases and other activities.\n\u2022 Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery.\n\u2022 Entering and managing trouble tickets for platform performance or data collection issues across the entire stack with internal and external support teams.\n\u2022 Monitoring and optimizing platform performance.\n\u2022 Communicating project status, timelines, deliverables, and roadblocks to partners and team members.\n\u2022 Testing and enabling AI and Machine Learning features, built by internal teams or embedded within the platforms, to evolve platform capabilities.\n\u2022 Partnering with internal SMEs to create, document, and maintain data governance practices, ensuring data quality, integrity, and compliance with privacy regulations (e.g., GDPR, CCPA).\n\u2022 Contributing to standards and best practices, fostering consistency and efficiency.\n\u2022 Providing training and support to internal stakeholders.\n\u2022 Providing recommendations for business process redesign and best practices; creating documentation as needed.\n\u2022 Establishing strong relationships with internal stakeholders and partners.\n\u2022 Staying up to date with industry trends, best practices, and emerging technologies related to customer data management and personalization.",
"word_count": 335
}
],
"urls": []
},
"rejected": false,
"rejection_reason": null,
"run_id": "8fbfdf67-0873-427e-aeef-1556f3bedbcf",
"stage3_signals": {
"alias_found": false,
"alias_match_roles": [],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Collaborating closely with cross-functional teams, including Analytics, AI\u0026D, Business Intelligence, and Enterprise Architecture, to identify and document data requirements and implement effective and compliant data collection strategies like tagging, streaming, or batch delivery.",
"similarity": 0.7052
},
{
"kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
"sentence": "Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery.",
"similarity": 0.6297
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "As a data-driven team member, youll work closely with data, development, analytics, AI, marketing, and other partners to build, implement, and maintain solutions to support personalized journeys and experiences.",
"similarity": 0.5662
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.6337,
"slug": "data-engineer",
"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 internal teams to understand business requirements for personalization and segmentation use cases, then translating them into technical specification documentation and writing technical user stories for development teams.",
"similarity": 0.5909
},
{
"kra_text": "Delivers features through CI/CD pipelines using automated tests, staged rollouts, feature flags, and incremental deployments.",
"sentence": "Testing and enabling AI and Machine Learning features, built by internal teams or embedded within the platforms, to evolve platform capabilities.",
"similarity": 0.5354
},
{
"kra_text": "Debugs full-stack issues that span frontend rendering, API behavior, database queries, and infrastructure configuration to identify root causes.",
"sentence": "Entering and managing trouble tickets for platform performance or data collection issues across the entire stack with internal and external support teams.",
"similarity": 0.5279
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 15,
"score": 0.5514,
"slug": "full-stack-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "optimize responsiveness and performance",
"sentence": "Monitoring and optimizing platform performance.",
"similarity": 0.6172
},
{
"kra_text": "translate product and design requirements",
"sentence": "Working with internal teams to understand business requirements for personalization and segmentation use cases, then translating them into technical specification documentation and writing technical user stories for development teams.",
"similarity": 0.5017
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborating closely with cross-functional teams, including Analytics, AI\u0026D, Business Intelligence, and Enterprise Architecture, to identify and document data requirements and implement effective and compliant data collection strategies like tagging, streaming, or batch delivery.",
"similarity": 0.4937
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5375,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "DevOps Engineer",
"kra_matches": [
{
"kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
"sentence": "Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery.",
"similarity": 0.5929
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Contributing to standards and best practices, fostering consistency and efficiency.",
"similarity": 0.5113
},
{
"kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
"sentence": "Monitoring and optimizing platform performance.",
"similarity": 0.5082
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.5375,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "Backend Developer",
"kra_matches": [
{
"kra_text": "Investigates and resolves production incidents, API bugs, and service degradation through root cause analysis, hotfixes, and post-mortems.",
"sentence": "Entering and managing trouble tickets for platform performance or data collection issues across the entire stack with internal and external support teams.",
"similarity": 0.5576
},
{
"kra_text": "Identifies and resolves backend performance bottlenecks through query optimization, indexing strategies, connection pooling, and distributed caching with Redis.",
"sentence": "Monitoring and optimizing platform performance.",
"similarity": 0.5453
},
{
"kra_text": "Investigates and resolves production incidents, API bugs, and service degradation through root cause analysis, hotfixes, and post-mortems.",
"sentence": "Actively monitoring and troubleshooting data collection, data pipelines, and connector issues across the tech stack, ensuring the integrity and reliability for data delivery.",
"similarity": 0.5004
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 1,
"score": 0.5344,
"slug": "backend-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "ML Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 3,
"score": 0.0588,
"slug": "ml-engineer",
"total_count": 17
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"GDPR"
],
"role_id": 5,
"score": 0.0588,
"slug": "cybersecurity-engineer",
"total_count": 17
},
{
"display_name": "AI Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 13,
"score": 0.0588,
"slug": "ai-engineer",
"total_count": 17
},
{
"display_name": "MLOps Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Machine Learning"
],
"role_id": 16,
"score": 0.0588,
"slug": "ml-ops-engineer",
"total_count": 17
},
{
"display_name": "Cloud Security Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"GDPR"
],
"role_id": 23,
"score": 0.0588,
"slug": "cloud-security-engineer",
"total_count": 17
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "DOMAIN",
"chosen_role": {
"display_name": "Business Analyst (Tech)",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 114,
"score": 0.77,
"slug": "business-analyst-tech",
"total_count": null
},
"confidence": 0.77,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [
"Marketing technology analysis",
"Personalization and segmentation enablement",
"Cross-functional requirements translation",
"Platform configuration support",
"Data collection and pipeline troubleshooting",
"Documentation and process mapping"
],
"matched_kras": [
"Translate business requirements into technical specifications",
"Write technical user stories for development teams",
"Document architecture, data flows, processes, and configurations",
"Maintain a data dictionary for marketing automation platform and CDP",
"Assist with CDP and marketing automation platform configuration",
"Participate in User Acceptance Testing (UAT)",
"Monitor and troubleshoot data collection, data pipelines, and connector issues",
"Enter and manage trouble tickets for platform issues"
],
"matched_skills": [
"identity resolution",
"real-time events",
"data flows",
"customer data platforms (CDPs)",
"marketing automation platforms",
"digital marketing",
"technical specification documentation",
"technical user stories",
"UAT",
"data dictionary"
],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Domain=Tech-Adjacent; The role is centered on translating personalization and segmentation business needs into technical specs, user stories, documentation, and cross-functional coordination, which best matches a technical business analyst.",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 9,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": {
"best_kra_similarity": 0.0,
"queue_id": 1979,
"r_and_r_preview": "As a part of the AI, Martech, and Personalization team, youll act as a bridge between marketing, data, and development teams. Youll play a part in our mission to drive data-powered marketing by enabli",
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"status": "pending"
},
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 25371,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Customer Data Platforms",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25372,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Marketing Automation Platforms",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25373,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Identity Resolution",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25374,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Real-time Events",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25375,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Data Flows",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25376,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Segmentation",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25377,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Automation",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25378,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Dynamic Personalization",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25379,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Tagging",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25380,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Streaming",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25381,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Batch Delivery",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25382,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "User Acceptance Testing",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25383,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "Data Governance",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 25384,
"role_display_name": "Business Analyst (Tech)",
"role_slug": "business-analyst-tech",
"skill_name": "CCPA",
"status": "pending"
}
],
"queue_entry_id": null,
"v3_pipeline_triggered": false,
"v3_role_slug": null,
"v3_run_id": null
}
}
API 2 — extract-details
{
"alias_matches": [
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 1990,
"existing_alias_text": "AI",
"input_term": "AI",
"matched_canonical": {
"category_id": 2,
"display_name": "AI",
"id": 1347,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "ai",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 2015,
"existing_alias_text": "Machine Learning",
"input_term": "Machine Learning",
"matched_canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
},
{
"alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
"alias_persisted": false,
"existing_alias_id": 718,
"existing_alias_text": "GDPR",
"input_term": "GDPR",
"matched_canonical": {
"category_id": 12,
"display_name": "GDPR",
"id": 402,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "STANDARD",
"slug": "gdpr",
"sub_category_id": 3215,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "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"
},
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
},
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
},
{
"display_name": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"source": "db"
},
{
"display_name": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
}
],
"chosen_role": {
"display_name": "Business Analyst (Tech)",
"id": 114,
"rationale": "Domain=Tech-Adjacent; The role is centered on translating personalization and segmentation business needs into technical specs, user stories, documentation, and cross-functional coordination, which best matches a technical business analyst.",
"role_archetype": null,
"slug": "business-analyst-tech",
"source": "db"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "AI",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Compliance and Security Frameworks",
"id": 73,
"rationale": "Formal control frameworks and regulatory standards used to assess and document security posture. This dimension is coherent because the role translates technical controls into auditable requirements and evidence.",
"slug": "compliance-and-security-frameworks",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Standards, Protocols \u0026 Compliance",
"id": 452,
"rationale": "Ensure teams adhere to industry standards, security protocols, and regulatory compliance requirements.",
"slug": "standards-protocols-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards \u0026 Compliance",
"id": 343,
"rationale": "Ensuring WordPress sites adhere to web markup, styling, accessibility, and privacy regulations.",
"slug": "web-standards-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards, Protocols \u0026 Compliance",
"id": 436,
"rationale": "Adhering to industry standards and regulatory compliance when designing and integrating storefront solutions.",
"slug": "web-standards-protocols-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
}
]
}
],
"input_final_skills": [
"Customer Data Platforms",
"Marketing Automation Platforms",
"Identity Resolution",
"Real-time Events",
"Data Flows",
"Segmentation",
"Automation",
"Dynamic Personalization",
"Tagging",
"Streaming",
"Batch Delivery",
"User Acceptance Testing",
"AI",
"Machine Learning",
"Data Governance",
"GDPR",
"CCPA"
],
"input_llm_skills": [
"Customer Data Platforms",
"Marketing Automation Platforms",
"Identity Resolution",
"Real-time Events",
"Data Flows",
"Segmentation",
"Automation",
"Dynamic Personalization",
"Tagging",
"Streaming",
"Batch Delivery",
"User Acceptance Testing",
"AI",
"Machine Learning",
"Data Governance",
"GDPR",
"CCPA"
],
"new_aliases_persisted": 0,
"run_id": "8fbfdf67-0873-427e-aeef-1556f3bedbcf",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Customer Data Platforms",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "customer-data-platforms",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Marketing Automation Platforms",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Cloud Platforms",
"skill_nature": "PLATFORM",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "marketing-automation-platforms",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Identity Resolution",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "identity-resolution",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Real-time Events",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "real-time-events",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Flows",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "data-flows",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Segmentation",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "segmentation",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Automation",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "automation",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Dynamic Personalization",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "dynamic-personalization",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Tagging",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "tagging",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Streaming",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "streaming",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Batch Delivery",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "batch-delivery",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "User Acceptance Testing",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Practices",
"skill_nature": "PRACTICE",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "user-acceptance-testing",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "AI",
"alias_type": "CANONICAL",
"id": 1990,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "AI",
"id": 1347,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "ai",
"sub_category_id": 1020,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "AI",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "AI",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Machine Learning",
"alias_type": "CANONICAL",
"id": 2015,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Machine Learning",
"id": 1356,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "machine-learning",
"sub_category_id": 1024,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": [
{
"display_name": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "db"
},
{
"display_name": "ML Engineer",
"id": 3,
"rationale": null,
"role_archetype": null,
"slug": "ml-engineer",
"source": "db"
},
{
"display_name": "MLOps Engineer",
"id": 16,
"rationale": null,
"role_archetype": null,
"slug": "ml-ops-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "React Frontend Development",
"id": 96,
"rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
"slug": "d_init_01",
"source": "db"
},
"input_skill": "Machine Learning",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "Machine Learning",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Governance",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Concepts",
"skill_nature": "CONCEPT",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "data-governance",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "GDPR",
"alias_type": "CANONICAL",
"id": 718,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 12,
"display_name": "GDPR",
"id": 402,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "STANDARD",
"slug": "gdpr",
"sub_category_id": 3215,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Compliance and Security Frameworks",
"id": 73,
"rationale": "Formal control frameworks and regulatory standards used to assess and document security posture. This dimension is coherent because the role translates technical controls into auditable requirements and evidence.",
"slug": "compliance-and-security-frameworks",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Cloud Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Standards, Protocols \u0026 Compliance",
"id": 452,
"rationale": "Ensure teams adhere to industry standards, security protocols, and regulatory compliance requirements.",
"slug": "standards-protocols-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards \u0026 Compliance",
"id": 343,
"rationale": "Ensuring WordPress sites adhere to web markup, styling, accessibility, and privacy regulations.",
"slug": "web-standards-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards, Protocols \u0026 Compliance",
"id": 436,
"rationale": "Adhering to industry standards and regulatory compliance when designing and integrating storefront solutions.",
"slug": "web-standards-protocols-compliance",
"source": "db"
},
"input_skill": "GDPR",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
}
]
}
],
"input_skill": "GDPR",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "CCPA",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Credentials",
"skill_nature": "CREDENTIAL",
"sub_category": "general",
"typical_lifespan": "MULTI_YEAR",
"version_strategy": "UNVERSIONED",
"volatility": "MEDIUM"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "ccpa",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Customer Data Platforms",
"Marketing Automation Platforms",
"Identity Resolution",
"Real-time Events",
"Data Flows",
"Segmentation",
"Automation",
"Dynamic Personalization",
"Tagging",
"Streaming",
"Batch Delivery",
"User Acceptance Testing",
"Data Governance",
"CCPA"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Business Analyst (Tech)",
"id": 114,
"rationale": "Domain=Tech-Adjacent; The role is centered on translating personalization and segmentation business needs into technical specs, user stories, documentation, and cross-functional coordination, which best matches a technical business analyst.",
"role_archetype": null,
"slug": "business-analyst-tech",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "Customer Data Platforms",
"tag": "new"
},
{
"skill": "Marketing Automation Platforms",
"tag": "new"
},
{
"skill": "Identity Resolution",
"tag": "new"
},
{
"skill": "Real-time Events",
"tag": "new"
},
{
"skill": "Data Flows",
"tag": "new"
},
{
"skill": "Segmentation",
"tag": "new"
},
{
"skill": "Automation",
"tag": "new"
},
{
"skill": "Dynamic Personalization",
"tag": "new"
},
{
"skill": "Tagging",
"tag": "new"
},
{
"skill": "Streaming",
"tag": "new"
},
{
"skill": "Batch Delivery",
"tag": "new"
},
{
"skill": "User Acceptance Testing",
"tag": "new"
},
{
"skill": "AI",
"tag": "in_db"
},
{
"skill": "Machine Learning",
"tag": "in_db"
},
{
"skill": "Data Governance",
"tag": "new"
},
{
"skill": "GDPR",
"tag": "in_db"
},
{
"skill": "CCPA",
"tag": "new"
}
],
"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": 114,
"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": "AI",
"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": 1347,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "AI Governance and Model Security",
"id": 50,
"rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
"slug": "ai-governance-and-model-security",
"source": "db"
},
"dimension_id": 50,
"input_skill": "Machine Learning",
"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": "AI Engineer",
"id": 13,
"rationale": null,
"role_archetype": null,
"slug": "ai-engineer",
"source": "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": 1356,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"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": "Machine Learning",
"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": 1356,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Compliance and Security Frameworks",
"id": 73,
"rationale": "Formal control frameworks and regulatory standards used to assess and document security posture. This dimension is coherent because the role translates technical controls into auditable requirements and evidence.",
"slug": "compliance-and-security-frameworks",
"source": "db"
},
"dimension_id": 73,
"input_skill": "GDPR",
"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 Security Engineer",
"id": 23,
"rationale": null,
"role_archetype": null,
"slug": "cloud-security-engineer",
"source": "db"
},
{
"display_name": "Cyber Security Engineer",
"id": 5,
"rationale": null,
"role_archetype": null,
"slug": "cybersecurity-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 402,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Standards, Protocols \u0026 Compliance",
"id": 452,
"rationale": "Ensure teams adhere to industry standards, security protocols, and regulatory compliance requirements.",
"slug": "standards-protocols-compliance",
"source": "db"
},
"dimension_id": 452,
"input_skill": "GDPR",
"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": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
},
{
"display_name": "Sitecore Dev",
"id": 233,
"rationale": null,
"role_archetype": "Engineering",
"slug": "sitecore-dev",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 402,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards \u0026 Compliance",
"id": 343,
"rationale": "Ensuring WordPress sites adhere to web markup, styling, accessibility, and privacy regulations.",
"slug": "web-standards-compliance",
"source": "db"
},
"dimension_id": 343,
"input_skill": "GDPR",
"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": "WordPress Dev",
"id": 227,
"rationale": null,
"role_archetype": "Engineering",
"slug": "wordpress-dev",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 402,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 114,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Web Standards, Protocols \u0026 Compliance",
"id": 436,
"rationale": "Adhering to industry standards and regulatory compliance when designing and integrating storefront solutions.",
"slug": "web-standards-protocols-compliance",
"source": "db"
},
"dimension_id": 436,
"input_skill": "GDPR",
"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": "Shopify Dev",
"id": 230,
"rationale": null,
"role_archetype": "Engineering",
"slug": "shopify-dev",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 402,
"skill_tag": "in_db",
"skipped_reason": null
}
],
"new_skills_created": 0,
"role_dimension_saved": 0,
"skill_dimension_saved": 0,
"skipped": 0
},
"planner_output": null,
"run_id": "8fbfdf67-0873-427e-aeef-1556f3bedbcf"
}