Pipeline run
143c5f20-3b21-4bc9-958f-5c1568bbb111
Pipeline LLM cost (USD)
API 1: $0.0077
API 2: $0.0003
API 3: $0.0000
Total: $0.0080
Client output enrichment
v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA descriptionNature of work
· Data Engineering / BI Database Development
Build and maintain warehouse SQL/PLSQL logic for BI reporting layers: write queries, DDL/DML, stored procedures, triggers, and functions across MySQL/Oracle/SQL Server, with some shell scripting support.
""The data warehouse serves as the functional foundation for middleware BI environments that provide end users with reports, dashboards, and other interfaces""
Tech stack maturity
Mainstream Legacy
The primary skills focus on established relational database and SQL technologies like MySQL, PL/SQL, SQL Server, and SQL, which are widely used but generally associated with legacy or mainstream enterprise data platforms rather than cloud-native or bleeding-edge stacks.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
0.00 / 5
· Title match
· Has AI skill
· AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
—
Frameworks (×2):
—
Models / concepts (×3):
—
Evidence — skills matched in JD (11)
MySQL
Oracle
SQL
PL/SQL
SQL Server
Shell scripting
DDL
DML
Stored procedures
Triggers
Functions
Skill cluster (2 dimension groups, role-scoped)
Relational Database Usage
MySQL
Cross-cutting / unaligned
Oracle
SQL
PL/SQL
SQL Server
Shell scripting
DDL
DML
Stored procedures
Triggers
Functions
Show KRA description ↓
The data warehouse serves as the functional foundation for middleware BI environments that provide end users with reports, dashboards, and other interfaces
• Educational qualification: BE/ B.tech/ MCA/ M.tech
• 2+ years of experience in any one of MySQL and Oracle.
• 1+ year of experience in SQL / PLSQL / Other Database.
• 1+ year of experience in SQL Server/ Oracle Server.
• Experience in Query Language/programming
• Experience with stored procedures, triggers and functions
• Experience in DDL and DML statements
• Adequate knowledge of Shell scripting.
• Experience in MySQL is definitely an advantage
• High level of drive, initiative and self-motivation
• Ability to take internal and external stakeholders along
• Understanding of Technology and User Experience
• Love for simplifying
• Growth Mindset
• Willingness to experiment and improve continuously
Signals
Skill
node-backend-developer
0.18
Alias
data-engineer
1.00
KRA
svelte-frontend-developer
0.45
Post-classification
Centroidupdated · n=21
Alias collision log—
New-role queue—
New skills captured7
New KRA capturedyes
Captured for admin review
Oracle
primary
↔
Data Warehouse Engineer
pending
Shell scripting
primary
↔
Data Warehouse Engineer
pending
DDL
primary
↔
Data Warehouse Engineer
pending
DML
primary
↔
Data Warehouse Engineer
pending
Stored procedures
primary
↔
Data Warehouse Engineer
pending
Triggers
primary
↔
Data Warehouse Engineer
pending
Functions
primary
↔
Data Warehouse Engineer
pending
R&R fragment (sim 0.00)
↔
Data Warehouse Engineer
pending
The data warehouse serves as the functional foundation for middleware BI environments that provide end users with reports, dashboards, and other interfaces • Educational qualification: BE/ B.tech/ MC…
Status:
completed
Created: 2026-05-27T17:35:19.531774Z
Updated: 2026-05-27T17:36:09.766189Z
API 3 duration: 4047 ms
Flow
Current 3-step pipeline
1 POST /skills/extract-from-jd
2 POST /skills/extract-details
3 POST /skills/final-role-output
Role
Chosen role & resolution
Data Warehouse Engineer
domain · Data Engineering & Analytics CASE DOMAINslug: data-warehouse-engineer · id: 144 · source: db
Domain=Data Engineering & Analytics; The JD focuses on database/query development, stored procedures, SQL/PLSQL, DDL/DML, and shell scripting for a data warehouse environment, which best fits a Data Engineer rather than a BI or modeling role.
Matched skills
MySQLOracleSQLPLSQLSQL Serverstored procedurestriggersfunctionsDDLDMLShell scripting
Matched dimensions
Database EngineeringData Warehouse SupportSQL/PLSQL DevelopmentScripting and AutomationBI Data Foundation
Matched KRAs
Serve as the functional foundation for middleware BI environmentsProvide end users with reports, dashboards, and other interfacesExperience in any one of MySQL and OracleExperience with stored procedures, triggers and functionsExperience in DDL and DML statementsAdequate knowledge of Shell scripting
Resolution:
in_db
— role exists in library; skill↔dim and role↔dim links saved when applicable.
0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped
Job description
Title: DWH - Software Engineer (MySQL—Telco) About Us: Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid - Buy Now, Pay Later. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners. About the team: Telco business is still one of the revenue generating wing of the company. Its 20 years of leadership journey is what lays foundation for the Paytm current business. One97 Telco business is the current market leader in VAS – Value Added Services for the telecom operators. We create content for the telco's like Astrology services, Hellotunes etc. and the model is a shared revenue. We deliver mobile content and commerce services to millions of mobile consumers. Our business encompasses 20+ global operators and 100+ enterprise customers. About the role: The data warehouse serves as the functional foundation for middleware BI environments that provide end users with reports, dashboards, and other interfaces Expectations/ Requirements • Educational qualification: BE/ B.tech/ MCA/ M.tech • 2+ years of experience in any one of MySQL and Oracle. • 1+ year of experience in SQL / PLSQL / Other Database. • 1+ year of experience in SQL Server/ Oracle Server. • Experience in Query Language/programming • Experience with stored procedures, triggers and functions • Experience in DDL and DML statements • Adequate knowledge of Shell scripting. • Experience in MySQL is definitely an advantage Superpowers/ Skills that will help you succeed in this role • High level of drive, initiative and self-motivation • Ability to take internal and external stakeholders along • Understanding of Technology and User Experience • Love for simplifying • Growth Mindset • Willingness to experiment and improve continuously Why join us • A collaborative output driven program that brings cohesiveness across businesses through technology • Improve the average revenue per use by increasing the cross-sell opportunities • A solid 360 feedbacks from your peer teams on your support of their goals • Respect, that is earned, not demanded from your peers and manager Compensation: If you are the right fit, we believe in creating wealth for you with enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it. India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story!
Skills from this JD
Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.
MySQL
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: MySQL
id=17
· mysql
Aliases — catalog
- MySQL (CANONICAL) primary
Context tags (catalog)
ACID
ACID compliance
Backup
Data Warehousing
Database Design
ER Diagrams
EXPLAIN
Indexes
InnoDB
JOIN
Joins
MyISAM
Normalization
PHPMyAdmin
Query Optimization
Replication
SQL
SQL queries
Stored Procedures
Transactions
Triggers
backup
backup and restore
backup strategies
data modeling
data normalization
database design
database normalization
database schema
foreign keys
indexes
indexing
joins
master-slave
normalization
performance tuning
query optimization
read replicas
replication
schema design
schema management
sharding
stored procedures
transaction isolation
transaction management
transactions
triggers
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- Oracle Corporation
- License
- gpl_v2
- Year introduced
- 1995
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: MySQL appears in a large share of backend/DB job descriptions and remains a standard managed offering across AWS RDS, Cloud SQL, and Azure Database, indicating broad hiring-pipeline demand.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Data Modeling Catalog dimension db id 216
Library dimension (catalog)
Roles linked in library: Fullstack Developer, Fullstack Developer, PHP Backend Developer
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
-
Relational Database Usage Catalog dimension db id 371
Library dimension (catalog)
Roles linked in library: Go Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Oracle
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- Sub-category
- general
- Skill nature
- TOOL
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
SQL
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: SQL
id=101
· sql
Aliases — catalog
- SQL (CANONICAL) primary
Context tags (catalog)
ACID
CTE
DDL
DML
ETL
JOIN
MySQL
NoSQL
OLAP
ORM
PostgreSQL
SQL injection
SQLite
T-SQL
data modeling
data warehousing
database normalization
execution plan
indexing
joins
normalization
query optimization
stored procedures
subquery
transaction isolation
transaction management
window functions
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Query Language
- Vendor
- ANSI
- License
- unknown
- Year introduced
- 1974
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL appears in a large share of data, backend, and analytics job descriptions and remains the default query language for PostgreSQL, MySQL, and cloud warehouses like Snowflake/BigQuery.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 97
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Pega Programming Languages & DSLs Catalog dimension db id 267
Library dimension (catalog)
Roles linked in library: Pega Developer
-
Programming Languages & DSLs Catalog dimension db id 475
Library dimension (catalog)
Roles linked in library: Engineering Manager
-
Programming Languages for Data Work Catalog dimension db id 21
Library dimension (catalog)
Roles linked in library: Data Engineer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
|
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
PL/SQL
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: PL/SQL
id=1567
· pl-sql
Aliases — catalog
- PL/SQL (CANONICAL)
Context tags (catalog)
Oracle
PL/SQL blocks
SQL*Plus
bulk collect
cursors
data manipulation
data types
dynamic SQL
exception handling
functions
packages
performance tuning
stored procedures
transaction control
triggers
Stored enrichment (catalog DB)
- Category
- Language
- Sub-category
- Procedural Sql Language
- Vendor
- Oracle Corporation
- License
- proprietary
- Year introduced
- 1990
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: PL/SQL appears frequently in Oracle-focused job postings and remains a standard skill for Oracle database development and maintenance; it is not sunset or replaced by a newer successor.
Skill profile (library / DB)
- Skill nature
- LANGUAGE
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 6
- Sub-category id
- 1173
- 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) |
SQL Server
Primary
Library skill
API 3: existing canonical (in_db)
Existing skill (matched library)
Canonical: SQL Server
id=18
· sql-server
Aliases — catalog
- SQL Server (CANONICAL) primary
- SQL Server 2000 (VERSION)
- SQL Server 2005 (VERSION)
- SQL Server 2008 (VERSION)
- SQL Server 2012 (VERSION)
- SQL Server 2014 (VERSION)
- SQL Server 2016 (VERSION)
- SQL Server 2017 (VERSION)
- SQL Server 2019 (VERSION)
- SQL Server 2022 (VERSION)
- SQL Server 6.5 (VERSION)
- SQL Server 7.0 (VERSION)
Context tags (catalog)
Always On
CLR Integration
Clustered Index
ETL
Execution Plan
Linked Servers
Query Store
Replication
SQL Agent
SQL Server Agent
SQL Server Integration Services
SQL Server Management Studio
SQL Server Reporting Services
SSIS
SSMS
SSRS
Stored Procedures
T-SQL
TempDB
backup and recovery
backup and restore
clustering
data migration
data warehousing
database design
database normalization
indexing
performance tuning
query optimization
replication
stored procedures
transaction log
transaction logs
Stored enrichment (catalog DB)
- Category
- Datastore
- Sub-category
- Relational Database
- Vendor
- Microsoft
- License
- proprietary
- Year introduced
- 1989
- Confidence
- 0.99
- Version strategy
- NOT_APPLICABLE
Maturity reasoning: SQL Server appears in many enterprise job descriptions and remains a major Microsoft-supported RDBMS with active Azure SQL/SQL Server demand; it is a common hiring-pipeline staple, not a sunset technology.
Skill profile (library / DB)
- Skill nature
- TOOL
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Category id
- 3
- Sub-category id
- 29
- Extractable
- True
- Also category
- False
Dimensions (API 2 worklist)
-
Relational Database Design Catalog dimension db id 4
Library dimension (catalog)
Roles linked in library: .NET Backend Developer, Backend Developer, Kotlin Backend Developer, Node.js Backend Developer, Python Backend Developer, Ruby Backend Developer, Scala Backend Developer
API 3 link attempts (this skill)
| Dimension | Skill↔dim | Role↔dim | Outcome |
|---|---|---|---|
|
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Shell scripting
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Programming Languages
- Sub-category
- general
- Skill nature
- LANGUAGE
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
DDL
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
DML
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- STABLE
- Typical lifespan
- EVERGREEN
- Version strategy
- UNVERSIONED
Stored procedures
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Triggers
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- Sub-category
- general
- Skill nature
- CONCEPT
- Volatility
- MEDIUM
- Typical lifespan
- MULTI_YEAR
- Version strategy
- UNVERSIONED
Functions
Primary
New / orchestrated
API 3: new canonical path (new)
New / unmatched skill (orchestrated in API 2)
Skill enrichment (orchestrator / LLM)
No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).
Derived legacy fields
- Category
- Databases
- 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 |
|---|---|---|---|---|---|---|
| MySQL | in_db |
Relational Data Modeling
relational-data-modeling
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| MySQL | in_db |
Relational Database Usage
relational-database-usage
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Pega Programming Languages & DSLs
pega-programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages & DSLs
programming-languages-dsls
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL | in_db |
Programming Languages for Data Work
programming-languages-for-data-work
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| PL/SQL | in_db |
React Frontend Development
d_init_01
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) | |
| SQL Server | in_db |
Relational Database Design
relational-database-design
|
✓ | — | Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role) |
Library artifacts (this run)
| Kind | Detail | DB id |
|---|---|---|
| canonical_skill_proposed | Oracle | type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Shell scripting | type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR | |
| canonical_skill_proposed | DDL | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | DML | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN | |
| canonical_skill_proposed | Stored procedures | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Triggers | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR | |
| canonical_skill_proposed | Functions | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR |
nano JD Parser — gpt-4.1-nano click to toggle
RoleDWH - Software Engineer (MySQL—Telco)
CompanyPaytm
Experience2+ years of experience in any one of MySQL and Oracle.
DomainIT Services & Consulting
JD type
pass
Show raw JSON
{
"JD_type": "pass",
"about_company": {
"source_marker": {
"first_5_words": "Paytm is India\u2019s leading digital",
"last_5_words": "loans, sourced by its financial partners."
},
"text": "Paytm is India\u2019s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid - Buy Now, Pay Later. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks\u2019 financial instruments. To further enhance merchants\u2019 business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners.",
"word_count": 100
},
"certifications": [],
"company_name": "Paytm",
"ctc": null,
"domain": {
"primary": {
"aliases": [
"ITES",
"BPO"
],
"domain": "IT Services \u0026 Consulting"
},
"secondary": null
},
"education": [
{
"level": "Bachelor\u0027s",
"qualification": "BTECH/BE - Any Discipline",
"raw": "Educational qualification: BE/ B.tech/ MCA/ M.tech",
"requirement": "required"
}
],
"experience": {
"max": null,
"min": 2,
"raw": "2+ years of experience in any one of MySQL and Oracle."
},
"job_locations": [],
"role": "DWH - Software Engineer (MySQL\u2014Telco)",
"role_aliases": [
"Data Warehouse Engineer",
"Software Engineer",
"DWH Engineer"
],
"role_archetype": "Engineering",
"roles_and_responsibilities": [
{
"bullet_count": 0,
"heading": "About the role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "The data warehouse serves as",
"last_5_words": "reports, dashboards, and other interfaces"
},
"text": "The data warehouse serves as the functional foundation for middleware BI environments that provide end users with reports, dashboards, and other interfaces",
"word_count": 25
},
{
"bullet_count": 9,
"heading": "Expectations/ Requirements",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 Educational qualification: BE/ B.tech/",
"last_5_words": "is definitely an advantage"
},
"text": "\u2022 Educational qualification: BE/ B.tech/ MCA/ M.tech\n\u2022 2+ years of experience in any one of MySQL and Oracle.\n\u2022 1+ year of experience in SQL / PLSQL / Other Database.\n\u2022 1+ year of experience in SQL Server/ Oracle Server.\n\u2022 Experience in Query Language/programming\n\u2022 Experience with stored procedures, triggers and functions\n\u2022 Experience in DDL and DML statements\n\u2022 Adequate knowledge of Shell scripting.\n\u2022 Experience in MySQL is definitely an advantage",
"word_count": 83
},
{
"bullet_count": 6,
"heading": "Superpowers/ Skills that will help you succeed in this role",
"heading_was_present": true,
"source_marker": {
"first_5_words": "\u2022 High level of drive, initiative",
"last_5_words": "experiment and improve continuously"
},
"text": "\u2022 High level of drive, initiative and self-motivation\n\u2022 Ability to take internal and external stakeholders along\n\u2022 Understanding of Technology and User Experience\n\u2022 Love for simplifying\n\u2022 Growth Mindset\n\u2022 Willingness to experiment and improve continuously",
"word_count": 36
}
],
"urls": []
}
API 1 — extract-from-jd click to toggle
{
"final_skills": [
{
"is_primary": true,
"skill_name": "MySQL"
},
{
"is_primary": true,
"skill_name": "Oracle"
},
{
"is_primary": true,
"skill_name": "SQL"
},
{
"is_primary": true,
"skill_name": "PL/SQL"
},
{
"is_primary": true,
"skill_name": "SQL Server"
},
{
"is_primary": true,
"skill_name": "Shell scripting"
},
{
"is_primary": true,
"skill_name": "DDL"
},
{
"is_primary": true,
"skill_name": "DML"
},
{
"is_primary": true,
"skill_name": "Stored procedures"
},
{
"is_primary": true,
"skill_name": "Triggers"
},
{
"is_primary": true,
"skill_name": "Functions"
}
],
"jd_role": {
"display_name": "DWH - Software Engineer (MySQL\u2014Telco)",
"rationale": null,
"role_aliases": [
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API 2 — extract-details
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"display_name": "Programming Languages for Data Work",
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"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
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{
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}
]
},
{
"dimension": {
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"slug": "d_init_01",
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},
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},
{
"dimension": {
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},
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{
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},
{
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"source": "db"
},
{
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"slug": "kotlin-server-backend-developer",
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},
{
"display_name": "Node.js Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
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},
{
"display_name": "Python Backend Developer",
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},
{
"display_name": "Ruby Backend Developer",
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},
{
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}
]
}
],
"input_final_skills": [
"MySQL",
"Oracle",
"SQL",
"PL/SQL",
"SQL Server",
"Shell scripting",
"DDL",
"DML",
"Stored procedures",
"Triggers",
"Functions"
],
"input_llm_skills": [
"MySQL",
"Oracle",
"SQL",
"PL/SQL",
"SQL Server",
"Shell scripting",
"DDL",
"DML",
"Stored procedures",
"Triggers",
"Functions"
],
"new_aliases_persisted": 0,
"run_id": "143c5f20-3b21-4bc9-958f-5c1568bbb111",
"skills_detail": [
{
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{
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"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
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"is_extractable": true,
"skill_nature": "TOOL",
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"sub_category_id": 29,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
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"display_name": "Relational Data Modeling",
"id": 216,
"rationale": "Modeling and tuning relational persistence for backend features. PHP backend developers need this to shape schemas, indexes, transactions, and query-aware data structures that support application behavior.",
"slug": "relational-data-modeling",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Fullstack Developer",
"id": 15,
"rationale": null,
"role_archetype": null,
"slug": "full-stack-engineer",
"source": "db"
},
{
"display_name": "Fullstack Developer",
"id": 435,
"rationale": null,
"role_archetype": "Engineering",
"slug": "fullstack-developer",
"source": "db"
},
{
"display_name": "PHP Backend Developer",
"id": 86,
"rationale": null,
"role_archetype": "Engineering",
"slug": "php-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
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"display_name": "Relational Database Design",
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"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
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},
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"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
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"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
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"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
},
{
"dimension": {
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"display_name": "Relational Database Usage",
"id": 371,
"rationale": "Working effectively with operational relational databases from Go backend services. This includes schema-aware querying, indexing awareness, transactions, and understanding how service code interacts with PostgreSQL or similar systems.",
"slug": "relational-database-usage",
"source": "db"
},
"input_skill": "MySQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Go Backend Developer",
"id": 81,
"rationale": null,
"role_archetype": "Engineering",
"slug": "go-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "MySQL",
"matched_via": "alias",
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": null,
"source_tag": "db",
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},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Oracle",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
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"version_strategy": "UNVERSIONED",
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},
"enrichment": null,
"keep_log": [],
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"merge_log": [],
"placed": null,
"relationships": null,
"skill_id": "oracle",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [
{
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"id": 271,
"is_primary": true,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "SQL",
"id": 101,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "sql",
"sub_category_id": 97,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Pega Programming Languages \u0026 DSLs",
"id": 267,
"rationale": "Programming languages and domain-specific languages used in Pega development.",
"slug": "pega-programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Pega Developer",
"id": 24,
"rationale": null,
"role_archetype": null,
"slug": "pega-developer",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages \u0026 DSLs",
"id": 475,
"rationale": "Oversee and guide the selection and effective use of programming and domain\u2010specific languages in software projects.",
"slug": "programming-languages-dsls",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Engineering Manager",
"id": 121,
"rationale": null,
"role_archetype": null,
"slug": "engineering-manager",
"source": "db"
}
]
},
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Programming Languages for Data Work",
"id": 21,
"rationale": "Languages used to implement data pipelines, transformations, and operational glue. This is the primary coding surface for building ingestion, enrichment, and automation logic in data engineering.",
"slug": "programming-languages-for-data-work",
"source": "db"
},
"input_skill": "SQL",
"llm_role": null,
"roles_from_db": [
{
"display_name": "Data Engineer",
"id": 2,
"rationale": null,
"role_archetype": null,
"slug": "data-engineer",
"source": "db"
}
]
}
],
"input_skill": "SQL",
"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": "PL/SQL",
"alias_type": "CANONICAL",
"id": 2513,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 6,
"display_name": "PL/SQL",
"id": 1567,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "LANGUAGE",
"slug": "pl-sql",
"sub_category_id": 1173,
"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": "PL/SQL",
"llm_role": null,
"roles_from_db": []
}
],
"input_skill": "PL/SQL",
"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": "SQL Server",
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"id": 135,
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"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2000",
"alias_type": "VERSION",
"id": 138,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2005",
"alias_type": "VERSION",
"id": 139,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2008",
"alias_type": "VERSION",
"id": 140,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2012",
"alias_type": "VERSION",
"id": 141,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2014",
"alias_type": "VERSION",
"id": 142,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2016",
"alias_type": "VERSION",
"id": 143,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2017",
"alias_type": "VERSION",
"id": 144,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2019",
"alias_type": "VERSION",
"id": 145,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 2022",
"alias_type": "VERSION",
"id": 146,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 6.5",
"alias_type": "VERSION",
"id": 136,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
},
{
"alias_text": "SQL Server 7.0",
"alias_type": "VERSION",
"id": 137,
"is_primary": false,
"match_strategy": "CASE_INSENSITIVE"
}
],
"canonical": {
"category_id": 3,
"display_name": "SQL Server",
"id": 18,
"is_also_category": false,
"is_extractable": true,
"skill_nature": "TOOL",
"slug": "sql-server",
"sub_category_id": 29,
"typical_lifespan": "EVERGREEN",
"volatility": "STABLE"
},
"dimensions": [
{
"dimension": {
"difficulty_hint": "well_known",
"display_name": "Relational Database Design",
"id": 4,
"rationale": "Modeling and operating relational persistence for backend services. Includes schema design, normalization, indexing, transactions, and query tuning for operational data stores.",
"slug": "relational-database-design",
"source": "db"
},
"input_skill": "SQL Server",
"llm_role": null,
"roles_from_db": [
{
"display_name": ".NET Backend Developer",
"id": 83,
"rationale": null,
"role_archetype": "Engineering",
"slug": "dotnet-backend-developer",
"source": "db"
},
{
"display_name": "Backend Developer",
"id": 1,
"rationale": null,
"role_archetype": "A Backend Engineer designs, builds, and maintains the server-side logic and data handling that power applications and services. They focus on implementing reliable business functionality, integrating with other systems, and ensuring the backend is scalable, maintainable, and observable.",
"slug": "backend-engineer",
"source": "db"
},
{
"display_name": "Kotlin Backend Developer",
"id": 84,
"rationale": null,
"role_archetype": "Engineering",
"slug": "kotlin-server-backend-developer",
"source": "db"
},
{
"display_name": "Node.js Backend Developer",
"id": 82,
"rationale": null,
"role_archetype": "Engineering",
"slug": "node-backend-developer",
"source": "db"
},
{
"display_name": "Python Backend Developer",
"id": 80,
"rationale": null,
"role_archetype": "Engineering",
"slug": "python-backend-developer",
"source": "db"
},
{
"display_name": "Ruby Backend Developer",
"id": 85,
"rationale": null,
"role_archetype": "Engineering",
"slug": "ruby-backend-developer",
"source": "db"
},
{
"display_name": "Scala Backend Developer",
"id": 87,
"rationale": null,
"role_archetype": "Engineering",
"slug": "scala-backend-developer",
"source": "db"
}
]
}
],
"input_skill": "SQL Server",
"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": "Shell scripting",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Programming Languages",
"skill_nature": "LANGUAGE",
"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": "shell-scripting",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "DDL",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"skill_nature": "CONCEPT",
"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": "ddl",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "DML",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"skill_nature": "CONCEPT",
"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": "dml",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Stored procedures",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"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": "stored-procedures",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Triggers",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"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": "triggers",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
},
{
"aliases_in_db": [],
"canonical": null,
"dimensions": [],
"input_skill": "Functions",
"matched_via": null,
"new_alias_persisted": false,
"new_alias_text": null,
"new_skill_meta": {
"derived": {
"category": "Databases",
"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": "functions",
"split_log": [],
"typed": null,
"warnings": []
},
"source_tag": "llm",
"was_in_llm_skills": true
}
],
"unmatched_skills": [
"Oracle",
"Shell scripting",
"DDL",
"DML",
"Stored procedures",
"Triggers",
"Functions"
]
}
API 3 — final-role-output
{
"chosen_role": {
"display_name": "Data Warehouse Engineer",
"id": 144,
"rationale": "Domain=Data Engineering \u0026 Analytics; The JD focuses on database/query development, stored procedures, SQL/PLSQL, DDL/DML, and shell scripting for a data warehouse environment, which best fits a Data Engineer rather than a BI or modeling role.",
"role_archetype": null,
"slug": "data-warehouse-engineer",
"source": "db"
},
"chosen_role_resolution": "in_db",
"final_input_skills": [
{
"skill": "MySQL",
"tag": "in_db"
},
{
"skill": "Oracle",
"tag": "new"
},
{
"skill": "SQL",
"tag": "in_db"
},
{
"skill": "PL/SQL",
"tag": "in_db"
},
{
"skill": "SQL Server",
"tag": "in_db"
},
{
"skill": "Shell scripting",
"tag": "new"
},
{
"skill": "DDL",
"tag": "new"
},
{
"skill": "DML",
"tag": "new"
},
{
"skill": "Stored procedures",
"tag": "new"
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