Pipeline run

931abd6d-9080-4e51-8bcf-d31724936253

Pipeline LLM cost (USD)

API 1: $0.0051 API 2: $0.0006 API 3: $0.0000 Total: $0.0057

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description

role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd

Nature of work · Data pipeline development

Builds big-data analytics tools, APIs, and self-service web apps for very large structured datasets, while tuning SQL/ML and partnering with data scientists, architects, and business teams to improve complex processes.

"developing technical tools and programs to automate the data management process, integrating medium to large structured data sets"

Tech stack maturity

Mainstream Legacy cache hit

The skill mix centers on Hadoop, Spark, SQL Server, .NET, and older web technologies, which is characteristic of established mainstream enterprise stacks rather than cloud-native or bleeding-edge systems.

AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)

1.70 / 5

· Title match

✓ Has AI skill

✓ AI skill (primary)

· AI skill (secondary)

· On AI team

· Builds AI products

vocab breakdown (legacy)

Assistants (×1): —

Frameworks (×2): —

Models / concepts (×3): Machine Learning

Evidence — skills matched in JD (14)

SQL Server Teradata Hadoop Spark R Machine Learning SQL C# .NET HTML5 JavaScript Cloud Services Object Function Scripting Languages Client-side Framework

Skill cluster (6 dimension groups, role-scoped)

ETL and ELT Tooling

Hadoop Spark

AI Governance and Model Security

Machine Learning

C# and .NET Languages

JavaScript and TypeScript

JavaScript

Programming Languages for Data Work

SQL

Cross-cutting / unaligned

SQL Server Teradata R .NET HTML5 Cloud Services Object Function Scripting Languages Client-side Framework

Show KRA description ↓

As a Senior Data Engineering Advisor, you will be responsible for developing technical tools and programs to automate the data management process, integrating medium to large structured data sets. You will have the opportunity to partner with Data Scientists, Architects or Businesses to design strategic projects and improve complex processes. • Design and build analytics solutions that deliver transformative insights from extremely large data sets. • Design, develop, and implement web applications for self-service delivery of analytics. • Design and develop APIs, database objects, machine learning algorithms, and necessary server-side code to support applications. • Work closely with team members to quickly integrate new components and features into current application ecosystem. • Continuously evaluate industry trends for opportunities to utilize new technologies and methodologies, and implement these into the solution stack as appropriate. • 8 to 12 years of experience in the using Data engineering technologies, including Big Data Tools like SQL Server, Teradata, Hadoop, Spark, and R. • Experience in big data platforms and solution designs to both technical and non-technical stakeholders. • Experience in machine learning and ability to write, tune, and debug performant SQL. • Experience in full stack development using Object-Oriented languages like, C#, .NET, HTML5, JavaScript. • Experience in Cloud Services, or Object Function Scripting Languages • Demonstrated ability creating rich web interfaces using a modern client-side framework.

Signals

Skill ml-ops-engineer

0.27

Alias data-engineer

1.00

KRA data-engineer

0.56

Post-classification

Centroidupdated · n=26

Alias collision log#108

New-role queue—

New skills captured6

New KRA captured—

Captured for admin review

Teradata primary ↔ Data Engineer pending

.NET primary ↔ Data Engineer pending

HTML5 primary ↔ Data Engineer pending

Cloud Services ↔ Data Engineer pending

Object Function Scripting Languages ↔ Data Engineer pending

Client-side Framework ↔ Data Engineer pending

Status: completed Created: 2026-05-21T23:46:53.516197Z Updated: 2026-05-21T23:47:17.154804Z API 3 duration: 6860 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 Engineer

CASE D

slug: data-engineer · id: 2 · source: db

The primary skills of SQL Server, Teradata, Hadoop, Spark, R, and Machine Learning align closely with the responsibilities of a Data Engineer.

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

New skills

Skill↔dim saved

Role↔dim saved

Skipped

Job description

Job Title: Senior Advisor, Data Engineering

Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What’s more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.

Join us to do the best work of your career and make a profound social impact as a Senior Data Engineering Advisor on our Data Engineering Team in Bangalore.

What You’ll Achieve

You will:

• Design and build analytics solutions that deliver transformative insights from extremely large data sets.
• Design, develop, and implement web applications for self-service delivery of analytics.
• Design and develop APIs, database objects, machine learning algorithms, and necessary server-side code to support applications.
• Work closely with team members to quickly integrate new components and features into current application ecosystem.
• Continuously evaluate industry trends for opportunities to utilize new technologies and methodologies, and implement these into the solution stack as appropriate.

Take the first step towards your dream career

Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role:

Essential Requirements

• 8 to 12 years of experience in the using Data engineering technologies, including Big Data Tools like SQL Server, Teradata, Hadoop, Spark, and R.
• Experience in big data platforms and solution designs to both technical and non-technical stakeholders.
• Experience in machine learning and ability to write, tune, and debug performant SQL.
• Experience in full stack development using Object-Oriented languages like, C#, .NET, HTML5, JavaScript.
• Experience in Cloud Services, or Object Function Scripting Languages

Desirable Requirements

• Demonstrated ability creating rich web interfaces using a modern client-side framework.

Who We Are

We believe that each of us has the power to make an impact. That’s why we put our team members at the center of everything we do. If you’re looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we’re looking for you.

Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.

Application closing date: 19 Sep 2025

Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.

Job ID:R269114

Skills from this JD

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

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: 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)

Teradata 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

Hadoop Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: Hadoop id=1351 · hadoop

Aliases — catalog

Hadoop (CANONICAL)

Context tags (catalog)

Big Data Data Lake Distributed Computing ELT ETL Flume HDFS Hive Kafka MapReduce NoSQL Oozie Pig Spark Sqoop YARN

Stored enrichment (catalog DB)

Category: Framework
Sub-category: Data Processing Framework
Vendor: Apache Software Foundation
License: apache_2
Year introduced: 2006
Confidence: 0.90
Version strategy: NOT_APPLICABLE

Maturity reasoning: Job postings still mention Hadoop for legacy big-data stacks, but JD volume has fallen as Spark and cloud warehouses replaced MapReduce-era clusters.

Skill profile (library / DB)

Skill nature: FRAMEWORK
Volatility: STABLE
Typical lifespan: EVERGREEN
Category id: 5
Sub-category id: 91
Extractable: True
Also category: False

Dimensions (API 2 worklist)

ETL and ELT Tooling Catalog dimension db id 24

Library dimension (catalog)

Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
ETL and ELT Tooling etl-and-elt-tooling	✓	✓	Existing dimension (library) · Role↔dimension saved

Spark Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: Apache Spark id=1350 · apache-spark

Aliases — catalog

Apache Spark (CANONICAL)
apache spark 3 (VERSION)
spark (VERSION)
spark 3 (VERSION)
spark 3.x (VERSION)
spark3 (VERSION)

Context tags (catalog)

Apache Kafka Cluster Manager DAGScheduler Data Lake DataFrame ETL Hadoop MLlib Machine Learning PySpark RDD Scala Spark SQL Spark Streaming SparkSession

Stored enrichment (catalog DB)

Category: Framework
Sub-category: Distributed Data Processing Framework
Vendor: Apache Software Foundation
License: apache_2
Year introduced: 2010
Confidence: 0.94
Version strategy: SEPARATE_ENTITY
Version tag: 3.x

Maturity reasoning: Apache Spark appears in many data engineering JDs and remains a standard for distributed ETL/ELT; its GitHub and vendor ecosystem activity stay strong, with Databricks and cloud platforms still promoting it.

Skill profile (library / DB)

Skill nature: FRAMEWORK
Volatility: STABLE
Typical lifespan: EVERGREEN
Category id: 5
Sub-category id: 1021
Extractable: True
Also category: False

Dimensions (API 2 worklist)

ETL and ELT Tooling Catalog dimension db id 24

Library dimension (catalog)

Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
ETL and ELT Tooling etl-and-elt-tooling	✓	✓	Existing dimension (library) · Role↔dimension saved

R Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: R id=194 · r

Aliases — catalog

R (VERSION)
R 3 (VERSION)
R 3.x (VERSION)
R 4 (VERSION)
R 4.0 (VERSION)
R 4.1 (VERSION)
R 4.2 (VERSION)
R 4.3 (VERSION)
R 4.4 (VERSION)
R 4.x (VERSION)

Context tags (catalog)

Bioconductor CRAN R Markdown Shiny Tidyverse caret data.table dplyr ggplot2 glm lme4 lubridate rstan tidyr tidyverse

Stored enrichment (catalog DB)

Category: Language
Sub-category: Programming Language
Vendor: R Core Team
License: gpl_v2
Year introduced: 1993
Confidence: 0.99
Version strategy: SEPARATE_ENTITY
Version tag: R 4.x

Maturity reasoning: R appears in many data science, statistics, and analytics job postings, and CRAN remains active with broad package usage across academia and industry.

Skill profile (library / DB)

Skill nature: LANGUAGE
Volatility: STABLE
Typical lifespan: EVERGREEN
Category id: 6
Sub-category id: 96
Extractable: True
Also category: False

Dimensions (API 2 worklist)

Programming Languages for ML Systems Catalog dimension db id 39

Library dimension (catalog)

Roles linked in library: ML Engineer, ML Ops Engineer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
Programming Languages for ML Systems programming-languages-for-ml-systems	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Machine Learning Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: Machine Learning id=1356 · machine-learning

Aliases — catalog

Machine Learning (CANONICAL)

Context tags (catalog)

Keras PyTorch TensorFlow cross-validation data preprocessing ensemble methods feature engineering hyperparameter tuning model evaluation natural language processing neural networks reinforcement learning scikit-learn supervised learning unsupervised learning

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, ML Ops 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)

SQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: SQL id=101 · sql

Aliases — catalog

SQL (CANONICAL) primary

Context tags (catalog)

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

Stored enrichment (catalog DB)

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

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

Skill profile (library / DB)

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

Dimensions (API 2 worklist)

Pega Programming Languages & DSLs Catalog dimension db id 267

Library dimension (catalog)

Roles linked in library: Pega Developer
Programming Languages for Data Work Catalog dimension db id 21

Library dimension (catalog)

Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
Pega Programming Languages & DSLs pega-programming-languages-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for Data Work programming-languages-for-data-work	✓	✓	Existing dimension (library) · Role↔dimension saved

C# Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: C id=4 · c

Aliases — catalog

C# (CANONICAL) primary
C (CANONICAL)
C# 1 (VERSION)
C# 10 (VERSION)
C# 11 (VERSION)
C# 12 (VERSION)
C# 13 (VERSION)
C# 14 (VERSION)
C# 2 (VERSION)
C# 3 (VERSION)
C# 4 (VERSION)
C# 5 (VERSION)
C# 6 (VERSION)
C# 7 (VERSION)
C# 8 (VERSION)
C# 9 (VERSION)
C# latest (VERSION)
C#1 (VERSION)
C#10 (VERSION)
C#11 (VERSION)
C#12 (VERSION)
C#2 (VERSION)
C#3 (VERSION)
C#4 (VERSION)
C#5 (VERSION)
C#6 (VERSION)
C#7 (VERSION)
C#8 (VERSION)
C#9 (VERSION)
C++ (CANONICAL)
C++03 (VERSION)
C++11 (VERSION)
C++14 (VERSION)
C++17 (VERSION)
C++20 (VERSION)
C++23 (VERSION)
C++26 (VERSION)
C++98 (VERSION)
c sharp (VERSION)
c# (VERSION)
cpp03 (VERSION)
cpp11 (VERSION)
cpp14 (VERSION)
cpp17 (VERSION)
cpp20 (VERSION)
cpp23 (VERSION)
cpp26 (VERSION)
cpp98 (VERSION)
csharp (VERSION)
modern C++ (VERSION)

Context tags (catalog)

.NET ASP.NET Azure Boost C# 9 C11 C99 CLR CMake Entity Framework LINQ MSBuild MVC Makefile NuGet Qt RAII Roslyn STL TDD Unity Visual Studio WPF Web API WinForms Xamarin async/await attributes buffer overflow constexpr delegates dependency injection dynamic memory events free function pointer gcc gdb header files inline interfaces linker malloc memory leak memory management move semantics multithreading operator overloading pointer pointers preprocessor segmentation fault smart pointers stdio.h stdlib.h struct syntax error templates typedef xUnit

Stored enrichment (catalog DB)

Category: Language
Sub-category: Programming Language
Vendor: Microsoft
License: mit
Year introduced: 2000
Confidence: 0.99
Version strategy: SEPARATE_ENTITY
Version tag: latest

Maturity reasoning: C# is a mainstream hiring staple with high JD volume across .NET, Azure, and enterprise roles; Microsoft continues active platform investment in .NET, reinforcing broad adoption.

Skill profile (library / DB)

Skill nature: LANGUAGE
Volatility: STABLE
Typical lifespan: EVERGREEN
Category id: 6
Sub-category id: 96
Extractable: True
Also category: False

Dimensions (API 2 worklist)

Cross-Platform App Languages Catalog dimension db id 167

Library dimension (catalog)

Roles linked in library: Hybrid Mobile Developer
Programming Languages Catalog dimension db id 1

Library dimension (catalog)

Roles linked in library: Backend Developer, Fullstack Developer
Programming Languages for ML Systems Catalog dimension db id 39

Library dimension (catalog)

Roles linked in library: ML Engineer, ML Ops Engineer
Programming Languages for XR Catalog dimension db id 97

Library dimension (catalog)

Roles linked in library: AR/VR Engineer
React Frontend Development Catalog dimension db id 96

Library dimension (catalog)
Video Codec Languages and DSLs Catalog dimension db id 225

Library dimension (catalog)

Roles linked in library: Video Codec Engineer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
Cross-Platform App Languages cross-platform-app-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages programming-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for ML Systems programming-languages-for-ml-systems	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages for XR programming-languages-for-xr	✓	—	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)
Video Codec Languages and DSLs video-codec-languages-and-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

.NET 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: Frameworks
Sub-category: general
Skill nature: TOOL
Volatility: MEDIUM
Typical lifespan: MULTI_YEAR
Version strategy: UNVERSIONED

HTML5 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: Web Technologies
Sub-category: general
Skill nature: LANGUAGE
Volatility: STABLE
Typical lifespan: EVERGREEN
Version strategy: UNVERSIONED

JavaScript Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)

Canonical: JavaScript id=607 · javascript

Aliases — catalog

JavaScript (CANONICAL) primary
ES2015 (VERSION)
ES2016 (VERSION)
ES2017 (VERSION)
ES2018 (VERSION)
ES2019 (VERSION)
ES2020 (VERSION)
ES2021 (VERSION)
ES2022 (VERSION)
ES2023 (VERSION)
ES2024 (VERSION)
ES5 (VERSION)
ES6 (VERSION)
JavaScript ES2015 (VERSION)
JavaScript ES2020 (VERSION)
JavaScript ES6 (VERSION)
modern JavaScript (VERSION)

Context tags (catalog)

AJAX Angular Babel DOM DOM manipulation ES6 Express JSON Node.js REST RESTful React TypeScript Vue Vue.js Webpack async/await asynchronous callback callback functions closure event-driven jQuery npm promises

Stored enrichment (catalog DB)

Category: Language
Sub-category: Programming Language
Vendor: Mozilla
License: mpl
Year introduced: 1995
Confidence: 0.99
Version strategy: NOT_APPLICABLE

Maturity reasoning: JavaScript appears in a very high volume of job postings across frontend, backend, and full-stack roles, and remains a core language in major ecosystems like Node.js and React.

Skill profile (library / DB)

Skill nature: LANGUAGE
Volatility: STABLE
Typical lifespan: EVERGREEN
Category id: 6
Sub-category id: 96
Extractable: True
Also category: False

Dimensions (API 2 worklist)

Cross-Platform App Languages Catalog dimension db id 167

Library dimension (catalog)

Roles linked in library: Hybrid Mobile Developer
JavaScript and TypeScript Catalog dimension db id 114

Library dimension (catalog)

Roles linked in library: Frontend Developer
Pega Programming Languages & DSLs Catalog dimension db id 267

Library dimension (catalog)

Roles linked in library: Pega Developer
Programming Languages Catalog dimension db id 1

Library dimension (catalog)

Roles linked in library: Backend Developer, Fullstack Developer

API 3 link attempts (this skill)

Dimension	Skill↔dim	Role↔dim	Outcome
Cross-Platform App Languages cross-platform-app-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript and TypeScript javascript-and-typescript	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Pega Programming Languages & DSLs pega-programming-languages-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Programming Languages programming-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

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

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields

Category: Cloud Platforms
Sub-category: general
Skill nature: PLATFORM
Volatility: MEDIUM
Typical lifespan: MULTI_YEAR
Version strategy: UNVERSIONED

Object Function Scripting Languages Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields

Category: Programming Languages
Sub-category: general
Skill nature: LANGUAGE
Volatility: MEDIUM
Typical lifespan: MULTI_YEAR
Version strategy: UNVERSIONED

Client-side Framework Secondary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

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

Derived legacy fields

Category: Web Frameworks
Sub-category: general
Skill nature: TOOL
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
SQL Server	in_db	Relational Database Design relational-database-design	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Hadoop	in_db	ETL and ELT Tooling etl-and-elt-tooling	✓	✓	Existing dimension (library) · Role↔dimension saved
Spark	in_db	ETL and ELT Tooling etl-and-elt-tooling	✓	✓	Existing dimension (library) · Role↔dimension saved
R	in_db	Programming Languages for ML Systems programming-languages-for-ml-systems	✓	—	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)
SQL	in_db	Pega Programming Languages & DSLs pega-programming-languages-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
SQL	in_db	Programming Languages for Data Work programming-languages-for-data-work	✓	✓	Existing dimension (library) · Role↔dimension saved
C#	in_db	Cross-Platform App Languages cross-platform-app-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C#	in_db	Programming Languages programming-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C#	in_db	Programming Languages for ML Systems programming-languages-for-ml-systems	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C#	in_db	Programming Languages for XR programming-languages-for-xr	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C#	in_db	React Frontend Development d_init_01	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
C#	in_db	Video Codec Languages and DSLs video-codec-languages-and-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript	in_db	Cross-Platform App Languages cross-platform-app-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript	in_db	JavaScript and TypeScript javascript-and-typescript	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript	in_db	Pega Programming Languages & DSLs pega-programming-languages-dsls	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
JavaScript	in_db	Programming Languages programming-languages	✓	—	Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind	Detail	DB id
canonical_skill_proposed	Teradata \| type=Databases subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed	.NET \| type=Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed	HTML5 \| type=Web Technologies subtype=general nature=LANGUAGE lifespan=EVERGREEN
canonical_skill_proposed	Cloud Services \| type=Cloud Platforms subtype=general nature=PLATFORM lifespan=MULTI_YEAR
canonical_skill_proposed	Object Function Scripting Languages \| type=Programming Languages subtype=general nature=LANGUAGE lifespan=MULTI_YEAR
canonical_skill_proposed	Client-side Framework \| type=Web Frameworks subtype=general nature=TOOL lifespan=MULTI_YEAR

nano JD Parser — gpt-4.1-nano click to toggle

RoleSenior Advisor, Data Engineering

CompanyDell Technologies

Experience8 to 12 years of experience

DomainIT Services & Consulting

Location Bangalore, India

JD type pass

Show raw JSON

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API 1 — extract-from-jd click to toggle

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API 2 — extract-details

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            "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
            "slug": "programming-languages-for-ml-systems",
            "source": "db"
          },
          "input_skill": "C#",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Ops Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Programming Languages for XR",
            "id": 97,
            "rationale": "Primary implementation languages used to build immersive client features, interaction logic, and device-specific runtime behavior. This is the core coding surface for AR/VR experiences.",
            "slug": "programming-languages-for-xr",
            "source": "db"
          },
          "input_skill": "C#",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AR/VR Engineer",
              "id": 8,
              "rationale": null,
              "role_archetype": null,
              "slug": "ar-vr-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": "C#",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Video Codec Languages and DSLs",
            "id": 225,
            "rationale": "Implementation languages and codec-specific description languages used to build compression, decoding, and transform logic. This is the primary coding surface for codec behavior and bitstream manipulation.",
            "slug": "video-codec-languages-and-dsls",
            "source": "db"
          },
          "input_skill": "C#",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Video Codec Engineer",
              "id": 22,
              "rationale": null,
              "role_archetype": null,
              "slug": "video-codec-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "C#",
      "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": ".NET",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Frameworks",
          "skill_nature": "TOOL",
          "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": "net",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "HTML5",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Web Technologies",
          "skill_nature": "LANGUAGE",
          "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": "html5",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "JavaScript",
          "alias_type": "CANONICAL",
          "id": 1028,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2015",
          "alias_type": "VERSION",
          "id": 1031,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2016",
          "alias_type": "VERSION",
          "id": 1032,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2017",
          "alias_type": "VERSION",
          "id": 1033,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2018",
          "alias_type": "VERSION",
          "id": 1034,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2019",
          "alias_type": "VERSION",
          "id": 1035,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2020",
          "alias_type": "VERSION",
          "id": 1036,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2021",
          "alias_type": "VERSION",
          "id": 1037,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2022",
          "alias_type": "VERSION",
          "id": 1038,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2023",
          "alias_type": "VERSION",
          "id": 1039,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES2024",
          "alias_type": "VERSION",
          "id": 1040,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES5",
          "alias_type": "VERSION",
          "id": 1029,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "ES6",
          "alias_type": "VERSION",
          "id": 1030,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "JavaScript ES2015",
          "alias_type": "VERSION",
          "id": 1042,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "JavaScript ES2020",
          "alias_type": "VERSION",
          "id": 1043,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "JavaScript ES6",
          "alias_type": "VERSION",
          "id": 1041,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        },
        {
          "alias_text": "modern JavaScript",
          "alias_type": "VERSION",
          "id": 1044,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 6,
        "display_name": "JavaScript",
        "id": 607,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "LANGUAGE",
        "slug": "javascript",
        "sub_category_id": 96,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Cross-Platform App Languages",
            "id": 167,
            "rationale": "Languages used to implement shared mobile features across iOS and Android from a common codebase. This is the primary coding surface for hybrid app logic, UI behavior, and platform-specific branching.",
            "slug": "cross-platform-app-languages",
            "source": "db"
          },
          "input_skill": "JavaScript",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Hybrid Mobile Developer",
              "id": 11,
              "rationale": null,
              "role_archetype": null,
              "slug": "hybrid-mobile-developer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "JavaScript and TypeScript",
            "id": 114,
            "rationale": "Primary implementation languages for browser client code, UI logic, and shared frontend utilities. These languages are the main coding surface for building interactive web experiences in this role.",
            "slug": "javascript-and-typescript",
            "source": "db"
          },
          "input_skill": "JavaScript",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Frontend Developer",
              "id": 7,
              "rationale": null,
              "role_archetype": null,
              "slug": "frontend-engineer",
              "source": "db"
            }
          ]
        },
        {
          "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": "JavaScript",
          "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",
            "id": 1,
            "rationale": "Primary implementation languages used to build client and server feature code. Full stack engineers need enough fluency to move across layers and implement product behavior end to end.",
            "slug": "programming-languages",
            "source": "db"
          },
          "input_skill": "JavaScript",
          "llm_role": null,
          "roles_from_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": "Fullstack Developer",
              "id": 15,
              "rationale": null,
              "role_archetype": null,
              "slug": "full-stack-engineer",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "JavaScript",
      "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": "Cloud Services",
      "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": "cloud-services",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Object Function Scripting Languages",
      "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": "object-function-scripting-languages",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Client-side Framework",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Web Frameworks",
          "skill_nature": "TOOL",
          "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": "client-side-framework",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Teradata",
    ".NET",
    "HTML5",
    "Cloud Services",
    "Object Function Scripting Languages",
    "Client-side Framework"
  ]
}

API 3 — final-role-output

{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "The primary skills of SQL Server, Teradata, Hadoop, Spark, R, and Machine Learning align closely with the responsibilities of a Data Engineer.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "SQL Server",
      "tag": "in_db"
    },
    {
      "skill": "Teradata",
      "tag": "new"
    },
    {
      "skill": "Hadoop",
      "tag": "in_db"
    },
    {
      "skill": "Spark",
      "tag": "in_db"
    },
    {
      "skill": "R",
      "tag": "in_db"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "C#",
      "tag": "in_db"
    },
    {
      "skill": ".NET",
      "tag": "new"
    },
    {
      "skill": "HTML5",
      "tag": "new"
    },
    {
      "skill": "JavaScript",
      "tag": "in_db"
    },
    {
      "skill": "Cloud Services",
      "tag": "new"
    },
    {
      "skill": "Object Function Scripting Languages",
      "tag": "new"
    },
    {
      "skill": "Client-side Framework",
      "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": "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"
        },
        "dimension_id": 4,
        "input_skill": "SQL Server",
        "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": "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 18,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Hadoop",
        "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": 1351,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "ETL and ELT Tooling",
          "id": 24,
          "rationale": "Packaged tools for extracting, loading, and transforming data across systems. This dimension covers connector-based ingestion, transformation frameworks, and managed integration products.",
          "slug": "etl-and-elt-tooling",
          "source": "db"
        },
        "dimension_id": 24,
        "input_skill": "Spark",
        "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": 1350,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Programming Languages for ML Systems",
          "id": 39,
          "rationale": "Languages used to build training code, inference services, evaluation jobs, and ML glue code. This is the primary implementation surface for ML engineers across experimentation and productionization.",
          "slug": "programming-languages-for-ml-systems",
          "source": "db"
        },
        "dimension_id": 39,
        "input_skill": "R",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Ops Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 194,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "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": "ML Ops 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": 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": "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": 2,
        "dimension": {
          "difficulty_hint": "well_known",
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}

LLM Calls

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

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