Pipeline run
f81487ca-532e-4f5f-ba28-89ef80544cd0
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
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Data Engineer
CASE Aslug: data-engineer · id: 2 · source: db
Exact alias hit on data-engineer (1.0) — no other alias at this confidence; skill_top data-engineer 0.11 does not contradict
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
Job description
Skills: Cybersecurity Data Engineer, Data Security, Python Java Scala, Database systems data warehousing, Data Integration, Data Pipeline, Greetings from Netsach - A Cyber Security Company. Position Overview: The Data Engineer will be responsible for designing, developing, and maintaining data pipelines and systems to ensure secure, reliable, and efficient data processing. This role involves working closely with data scientists, security analysts, and other stakeholders to support our cybersecurity initiatives. Job Title: Data Engineer Exp: 7yrs Location: Bangalore Onsite Interested candidates please share your updated resume at emily@netsach.co.in. Looking for immediate joiners /15 days. Key Responsibilities Data Pipeline Development: • Design and build scalable data pipelines to collect, process, and analyze large volumes of security-related data. • Implement ETL (Extract, Transform, Load) processes to ensure data integrity and quality. Data Security • Ensure data pipelines and storage solutions comply with security standards and best practices. • Implement data encryption, masking, and access control mechanisms. Integration • Integrate data from various sources, including logs, databases, and external APIs. • Ensure seamless data flow between systems and applications. Collaboration • Work closely with data scientists and security analysts to understand data requirements and deliver solutions. • Collaborate with IT and cybersecurity teams to ensure data infrastructure aligns with security needs. Performance Optimization • Monitor and optimize the performance of data pipelines and systems. • Troubleshoot and resolve data processing issues. Data Quality • Implement data validation and monitoring to ensure data accuracy and consistency. • Develop and enforce data quality standards and best practices. Documentation • Maintain comprehensive documentation of data pipelines, processes, and security measures. • Prepare reports on data processing and security status. Technology Evaluation • Evaluate and recommend new tools and technologies to enhance data processing and security capabilities. • Stay updated with the latest trends and advancements in data engineering and cybersecurity. Qualifications • Education: • Bachelors degree in Computer Science, Information Technology, Cyber Security, Data Engineering, or a related field. • Experience: • Proven experience in data engineering, with a focus on building and managing data pipelines. • Strong background in cybersecurity or a related field is preferred. • Skills: • Proficiency in programming languages such as Python, Java, or Scala. • Experience with data processing frameworks such as Apache Spark, Hadoop, or similar. • Knowledge of database systems (SQL, NoSQL) and data warehousing solutions. • Understanding of data security principles and best practices. • Excellent problem-solving, analytical, and communication skills. • Certifications: • Relevant certifications such as CDP, CISSP, or equivalent are a plus. Thank You Emily Jha emily@netsach.co.in Netsach - A Cyber Security Company www.netsach.co.in
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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- PRACTICE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- APIs (CANONICAL)
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Protocol
- Sub-category
- Application Programming Interfaces
- Confidence
- 0.93
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: APIs are a hiring-pipeline staple across backend, mobile, and platform JDs; REST/GraphQL/API design appears in large volumes of job postings and vendor docs, indicating broad adoption.
Skill profile (library / DB)
- Skill nature
- PROTOCOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 10
- Sub-category id
- 902
- 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) |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Databases
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Security Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Aliases — catalog
- Data masking (CANONICAL) primary
Context tags (catalog)
Stored enrichment (catalog DB)
- Category
- Concept
- Sub-category
- Data Protection Concept
- Confidence
- 0.88
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: Common in security/compliance job descriptions and vendor docs for PCI/GDPR; often paired with DLP and tokenization in enterprise data platforms.
Skill profile (library / DB)
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 2
- Sub-category id
- 77
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Data Governance and Access Controls Catalog dimension db id 32
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Data Governance and Access Controls
data-governance-and-access-controls
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Security Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
- Category
- Data Engineering Tools
- 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
- Monitoring Tools
- 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
- Data Engineering Tools
- Sub-category
- general
- Skill nature
- CONCEPT
- 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 |
|---|---|---|---|---|---|---|
| APIs | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| Data Masking | in_db |
Data Governance and Access Controls
data-governance-and-access-controls
|
✓ | ✓ | Existing dimension (library) · Role↔dimension saved |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Databases | type=Databases subtype=general nature=TOOL lifespan=EVERGREEN | |
| canonical_skill_proposed | Data Encryption | type=Security Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Access Control | type=Security Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Validation | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Monitoring | type=Monitoring Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Data Quality | type=Data Engineering Tools subtype=general nature=CONCEPT 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": "Netsach - A Cyber Security",
"last_5_words": "Cyber Security Company"
},
"text": "Netsach - A Cyber Security Company",
"word_count": 7
},
"certifications": [
"CDP",
"CISSP"
],
"company_name": "Netsach",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Cyber Security",
"Information Security"
],
"domain": "Cybersecurity"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Information Technology / Cyber Security / Data Engineering (or related)",
"raw": "Bachelors degree in Computer Science, Information Technology, Cyber Security, Data Engineering, or a related field.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "7yrs"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Cybersecurity Data Engineer",
"Data Security Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 15,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Data Pipeline Development:\n\n\u2022 Design and",
"last_5_words": "data engineering and cybersecurity."
},
"text": "Data Pipeline Development:\n\n\u2022 Design and build scalable data pipelines to collect, process, and analyze large volumes of security-related data.\n\u2022 Implement ETL (Extract, Transform, Load) processes to ensure data integrity and quality.\n\nData Security\n\n\u2022 Ensure data pipelines and storage solutions comply with security standards and best practices.\n\u2022 Implement data encryption, masking, and access control mechanisms.\n\nIntegration\n\n\u2022 Integrate data from various sources, including logs, databases, and external APIs.\n\u2022 Ensure seamless data flow between systems and applications.\n\nCollaboration\n\n\u2022 Work closely with data scientists and security analysts to understand data requirements and deliver solutions.\n\u2022 Collaborate with IT and cybersecurity teams to ensure data infrastructure aligns with security needs.\n\nPerformance Optimization\n\n\u2022 Monitor and optimize the performance of data pipelines and systems.\n\u2022 Troubleshoot and resolve data processing issues.\n\nData Quality\n\n\u2022 Implement data validation and monitoring to ensure data accuracy and consistency.\n\u2022 Develop and enforce data quality standards and best practices.\n\nDocumentation\n\n\u2022 Maintain comprehensive documentation of data pipelines, processes, and security measures.\n\u2022 Prepare reports on data processing and security status.\n\nTechnology Evaluation\n\n\u2022 Evaluate and recommend new tools and technologies to enhance data processing and security capabilities.\n\u2022 Stay updated with the latest trends and advancements in data engineering and cybersecurity.",
"word_count": 366
}
],
"urls": [
{
"type": "website",
"url": "http://www.netsach.co.in"
}
]
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "ETL"
},
{
"is_primary": true,
"skill_name": "APIs"
},
{
"is_primary": true,
"skill_name": "Databases"
},
{
"is_primary": true,
"skill_name": "Data Encryption"
},
{
"is_primary": true,
"skill_name": "Data Masking"
},
{
"is_primary": true,
"skill_name": "Access Control"
},
{
"is_primary": true,
"skill_name": "Data Validation"
},
{
"is_primary": true,
"skill_name": "Data Monitoring"
},
{
"is_primary": true,
"skill_name": "Data Quality"
}
],
"jd_role": {
"display_name": "Data Engineer",
"rationale": null,
"role_aliases": [
"Data Engineer",
"Cybersecurity Data Engineer",
"Data Security Engineer"
],
"role_archetype": "Data",
"slug": ""
},
"nano_parsed": {
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Netsach - A Cyber Security",
"last_5_words": "Cyber Security Company"
},
"text": "Netsach - A Cyber Security Company",
"word_count": 7
},
"certifications": [
"CDP",
"CISSP"
],
"company_name": "Netsach",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"Cyber Security",
"Information Security"
],
"domain": "Cybersecurity"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Computer Science / Information Technology / Cyber Security / Data Engineering (or related)",
"raw": "Bachelors degree in Computer Science, Information Technology, Cyber Security, Data Engineering, or a related field.",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 7,
"raw": "7yrs"
},
"job_locations": [
{
"aliases": [
"Bengaluru"
],
"city": "Bangalore",
"country": "India",
"state": null,
"work_mode": "onsite"
}
],
"role": "Data Engineer",
"role_aliases": [
"Data Engineer",
"Cybersecurity Data Engineer",
"Data Security Engineer"
],
"role_archetype": "Data",
"roles_and_responsibilities": [
{
"bullet_count": 15,
"heading": "Key Responsibilities",
"heading_was_present": true,
"source_marker": {
"first_5_words": "Data Pipeline Development:\n\n\u2022 Design and",
"last_5_words": "data engineering and cybersecurity."
},
"text": "Data Pipeline Development:\n\n\u2022 Design and build scalable data pipelines to collect, process, and analyze large volumes of security-related data.\n\u2022 Implement ETL (Extract, Transform, Load) processes to ensure data integrity and quality.\n\nData Security\n\n\u2022 Ensure data pipelines and storage solutions comply with security standards and best practices.\n\u2022 Implement data encryption, masking, and access control mechanisms.\n\nIntegration\n\n\u2022 Integrate data from various sources, including logs, databases, and external APIs.\n\u2022 Ensure seamless data flow between systems and applications.\n\nCollaboration\n\n\u2022 Work closely with data scientists and security analysts to understand data requirements and deliver solutions.\n\u2022 Collaborate with IT and cybersecurity teams to ensure data infrastructure aligns with security needs.\n\nPerformance Optimization\n\n\u2022 Monitor and optimize the performance of data pipelines and systems.\n\u2022 Troubleshoot and resolve data processing issues.\n\nData Quality\n\n\u2022 Implement data validation and monitoring to ensure data accuracy and consistency.\n\u2022 Develop and enforce data quality standards and best practices.\n\nDocumentation\n\n\u2022 Maintain comprehensive documentation of data pipelines, processes, and security measures.\n\u2022 Prepare reports on data processing and security status.\n\nTechnology Evaluation\n\n\u2022 Evaluate and recommend new tools and technologies to enhance data processing and security capabilities.\n\u2022 Stay updated with the latest trends and advancements in data engineering and cybersecurity.",
"word_count": 366
}
],
"urls": [
{
"type": "website",
"url": "http://www.netsach.co.in"
}
]
},
"rejected": false,
"rejection_reason": null,
"run_id": "f81487ca-532e-4f5f-ba28-89ef80544cd0",
"stage3_signals": {
"alias_found": true,
"alias_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
}
],
"kra_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": [
{
"kra_text": "Implements data quality validation rules, reconciliation checks, and anomaly detection to ensure data completeness, accuracy, and consistency.",
"sentence": "Implement data validation and monitoring to ensure data accuracy and consistency.",
"similarity": 0.7227
},
{
"kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
"sentence": "Work closely with data scientists and security analysts to understand data requirements and deliver solutions.",
"similarity": 0.6929
},
{
"kra_text": "Monitors pipeline health, SLA breach alerts, and job failure notifications, and performs root cause analysis for data pipeline incidents.",
"sentence": "Monitor and optimize the performance of data pipelines and systems.",
"similarity": 0.672
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 0.6958,
"slug": "data-engineer",
"total_count": null
},
{
"display_name": "Flutter Developer",
"kra_matches": [
{
"kra_text": "integrate external APIs and data sources",
"sentence": "Integrate data from various sources, including logs, databases, and external APIs.",
"similarity": 0.7684
},
{
"kra_text": "collaborate with design, product, and backend teams",
"sentence": "Collaborate with IT and cybersecurity teams to ensure data infrastructure aligns with security needs.",
"similarity": 0.5047
},
{
"kra_text": "integrate external APIs and data sources",
"sentence": "Ensure seamless data flow between systems and applications.",
"similarity": 0.429
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 74,
"score": 0.5674,
"slug": "flutter-developer",
"total_count": null
},
{
"display_name": "Cyber Security Engineer",
"kra_matches": [
{
"kra_text": "Defines secure engineering standards, secure coding guidelines, threat intelligence feeds, and compliance requirements for the organization.",
"sentence": "Ensure data pipelines and storage solutions comply with security standards and best practices.",
"similarity": 0.5782
},
{
"kra_text": "Conducts security posture assessments, vulnerability scans, and penetration testing to identify weaknesses and evaluate overall system security.",
"sentence": "Prepare reports on data processing and security status.",
"similarity": 0.5635
},
{
"kra_text": "Performs threat modeling, security architecture reviews, and quantitative risk analysis for new product features and infrastructure changes.",
"sentence": "Evaluate and recommend new tools and technologies to enhance data processing and security capabilities.",
"similarity": 0.5396
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 5,
"score": 0.5604,
"slug": "cybersecurity-engineer",
"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": "Monitor and optimize the performance of data pipelines and systems.",
"similarity": 0.6469
},
{
"kra_text": "Collaborates with development teams to improve build processes, reduce deployment friction, containerize applications, and adopt DevOps best practices.",
"sentence": "Collaborate with IT and cybersecurity teams to ensure data infrastructure aligns with security needs.",
"similarity": 0.4967
},
{
"kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
"sentence": "Maintain comprehensive documentation of data pipelines, processes, and security measures.",
"similarity": 0.476
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 10,
"score": 0.5399,
"slug": "devops-engineer",
"total_count": null
},
{
"display_name": "MLOps Engineer",
"kra_matches": [
{
"kra_text": "Sets up model monitoring dashboards, data drift detection, prediction performance tracking, and alert routing for production ML systems.",
"sentence": "Monitor and optimize the performance of data pipelines and systems.",
"similarity": 0.5605
},
{
"kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
"sentence": "Implement data validation and monitoring to ensure data accuracy and consistency.",
"similarity": 0.5299
},
{
"kra_text": "Validates model performance benchmarks, data schema contracts, and system integration health before signing off on production release readiness.",
"sentence": "Develop and enforce data quality standards and best practices.",
"similarity": 0.5138
}
],
"matched_count": null,
"matched_skills": null,
"role_id": 16,
"score": 0.5348,
"slug": "ml-ops-engineer",
"total_count": null
}
],
"skill_match_roles": [
{
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": 1,
"matched_skills": [
"Data masking"
],
"role_id": 2,
"score": 0.1111,
"slug": "data-engineer",
"total_count": 9
}
]
},
"stage4_decision": {
"alias_collision_detected": false,
"case": "A",
"chosen_role": {
"display_name": "Data Engineer",
"kra_matches": null,
"matched_count": null,
"matched_skills": null,
"role_id": 2,
"score": 1.0,
"slug": "data-engineer",
"total_count": null
},
"confidence": 1.0,
"is_new_role": false,
"llm2_fired": false,
"llm2_reasoning": null,
"matched_dimensions": [],
"matched_kras": [],
"matched_skills": [],
"new_role_display_name": null,
"new_role_slug": null,
"queued": false,
"reasoning": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.11 does not contradict",
"sub_role": null
},
"stage5_updates": {
"centroid_n_after": 435,
"centroid_updated": true,
"collision_log_id": null,
"new_kra_attached": null,
"new_skills_attached": [
{
"is_primary": true,
"queue_id": 20201,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "ETL",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20202,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Databases",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20203,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Encryption",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20204,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Access Control",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20205,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Validation",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20206,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Monitoring",
"status": "pending"
},
{
"is_primary": true,
"queue_id": 20207,
"role_display_name": "Data Engineer",
"role_slug": "data-engineer",
"skill_name": "Data Quality",
"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": 1828,
"existing_alias_text": "APIs",
"input_term": "APIs",
"matched_canonical": {
"category_id": 10,
"display_name": "APIs",
"id": 1192,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "apis",
"sub_category_id": 902,
"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": 364,
"existing_alias_text": "Data masking",
"input_term": "Data Masking",
"matched_canonical": {
"category_id": 2,
"display_name": "Data masking",
"id": 155,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "data-masking",
"sub_category_id": 77,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"matched_via": "alias"
}
],
"candidate_roles": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.11 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"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": "APIs",
"llm_role": null,
"roles_from_db": []
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Data Governance and Access Controls",
"id": 32,
"rationale": "Controls and policies for protecting sensitive data and managing who can see or use it. This includes classification, masking, row-level access, retention, and auditability for governed datasets.",
"slug": "data-governance-and-access-controls",
"source": "db"
},
"input_skill": "Data Masking",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_final_skills": [
"ETL",
"APIs",
"Databases",
"Data Encryption",
"Data Masking",
"Access Control",
"Data Validation",
"Data Monitoring",
"Data Quality"
],
"input_llm_skills": [
"ETL",
"APIs",
"Databases",
"Data Encryption",
"Data Masking",
"Access Control",
"Data Validation",
"Data Monitoring",
"Data Quality"
],
"new_aliases_persisted": 0,
"run_id": "f81487ca-532e-4f5f-ba28-89ef80544cd0",
"skills_detail": [
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "ETL",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"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": "etl",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "APIs",
"alias_type": "CANONICAL",
"id": 1828,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 10,
"display_name": "APIs",
"id": 1192,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "PROTOCOL",
"slug": "apis",
"sub_category_id": 902,
"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": "APIs",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "APIs",
"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": "Databases",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"skill_nature": "TOOL",
"sub_category": "general",
"typical_lifespan": "EVERGREEN",
"version_strategy": "UNVERSIONED",
"volatility": "STABLE"
},
"enrichment": null,
"keep_log": [],
"locked_dimensions": [],
"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "databases",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Encryption",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Security Tools",
"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-encryption",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
"alias_text": "Data masking",
"alias_type": "CANONICAL",
"id": 364,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 2,
"display_name": "Data masking",
"id": 155,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "CONCEPT",
"slug": "data-masking",
"sub_category_id": 77,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Data Governance and Access Controls",
"id": 32,
"rationale": "Controls and policies for protecting sensitive data and managing who can see or use it. This includes classification, masking, row-level access, retention, and auditability for governed datasets.",
"slug": "data-governance-and-access-controls",
"source": "db"
},
"input_skill": "Data Masking",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "Data Masking",
"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": "Access Control",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Security Tools",
"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": "access-control",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Validation",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"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": "data-validation",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Monitoring",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Monitoring Tools",
"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": "data-monitoring",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Data Quality",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Data Engineering Tools",
"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-quality",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"ETL",
"Databases",
"Data Encryption",
"Access Control",
"Data Validation",
"Data Monitoring",
"Data Quality"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Engineer",
"id": 2,
"rationale": "Exact alias hit on data-engineer (1.0) \u2014 no other alias at this confidence; skill_top data-engineer 0.11 does not contradict",
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "ETL",
"tag": "new"
},
{
"skill": "APIs",
"tag": "in_db"
},
{
"skill": "Databases",
"tag": "new"
},
{
"skill": "Data Encryption",
"tag": "new"
},
{
"skill": "Data Masking",
"tag": "in_db"
},
{
"skill": "Access Control",
"tag": "new"
},
{
"skill": "Data Validation",
"tag": "new"
},
{
"skill": "Data Monitoring",
"tag": "new"
},
{
"skill": "Data Quality",
"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": 2,
"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": "APIs",
"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": 1192,
"skill_tag": "in_db",
"skipped_reason": null
},
{
"chosen_role_id": 2,
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Data Governance and Access Controls",
"id": 32,
"rationale": "Controls and policies for protecting sensitive data and managing who can see or use it. This includes classification, masking, row-level access, retention, and auditability for governed datasets.",
"slug": "data-governance-and-access-controls",
"source": "db"
},
"dimension_id": 32,
"input_skill": "Data Masking",
"llm_role": null,
"matched_chosen_role": true,
"outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension saved",
"role_dimension_saved": true,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
],
"skill_dimension_saved": true,
"skill_id": 155,
"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": "f81487ca-532e-4f5f-ba28-89ef80544cd0"
}