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Pipeline run

3b41bee4-2730-47e1-845b-e5658db78eac

Pipeline LLM cost (USD)
API 1: $0.0111 API 2: $0.0011 API 3: $0.0000 Total: $0.0122

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
Nature of work
no_db_connection
Tech stack maturity
Mainstream Modern
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 (31)
PostgreSQL SQL Materialized Views Stored Procedures Functions Triggers ACID ORM Sharding Connection Pooling Change Data Capture Cron NoSQL Debezium Microservices ETL Prometheus Grafana pgBadger Data Encryption Access Control Auditing ISO 27001 GDPR DPDP +6
Skill cluster (0 dimension groups, role-scoped)
No dimension groups computed for this JD.
Show KRA description ↓
We are looking for a highly skilled Database Architect with deep expertise in PostgreSQL to design, optimize, and scale our mission-critical data systems. The ideal candidate will work closely with development and operations teams to define data models, tune SQL queries, and architect high-performance, scalable database solutions. This role focuses on database design, optimization, and performance engineering, while actively collaborating with the operations team to recommend tuning strategies and resolve database bottlenecks across environments. Conversant with NoSQL databases is plus. • Database Architecture & Design • Architect scalable, secure, and high-performance PostgreSQL database solutions for transactional and analytical systems. • Design and maintain logical and physical schemas, ensuring proper normalization, entity relationships, and data integrity without compromising performance. • Define database standards for naming conventions, indexing, constraints, partitioning, and query optimization. • Architect and maintain database-specific materialized views, stored procedures, functions, and triggers. • Oversee schema migrations, rollbacks, and version-controlled database evolution strategies. • Implement distributed transaction management and ensure ACID compliance across services. • Performance Optimization & Query Engineering • Analyze and tune complex SQL queries, joins, and stored procedures for high-throughput applications. • Define and monitor indexing strategies, query execution plans, and partitioning for large-scale datasets. • Lead query optimization, deadlock detection, and resolution strategies with development teams. • Collaborate with developers to optimize ORM configurations and reduce query overhead. • Design database caching and sharding strategies that align with application access patterns. • Review and recommend improvements for connection pooling configurations on the application side to ensure alignment with database capacity planning. • Data Modelling, Integrity & CDC Integration • Design conceptual, logical, and physical data models aligned with system requirements. • Ensure data consistency and integrity using constraints, foreign keys, and triggers. • Define and implement CDC (Change Data Capture) strategies using tools like Debezium for downstream synchronization and event-driven architectures. • Collaborate with data engineering teams to define ETL and CDC-based data flows between microservices and analytics pipelines for data warehousing use cases. • Monitoring, Dashboards & Alerting • Define and oversee database monitoring dashboards using tools like Prometheus, Grafana, or pgBadger. • Set up alerting rules for query latency, replication lag, deadlocks, and transaction bottlenecks. • Collaborate with operations teams to continuously improve observability, performance SLAs, and response metrics. • Perform Root Cause Analysis (RCA) for P1 production issues caused by database performance or query inefficiencies. • Conduct PostgreSQL log analysis to identify slow queries, locking patterns, and resource contention. • Recommend design-level and query-level corrective actions based on production RCA findings. • Regularly review metrics to anticipate and prevent scalability or resource utilization issues before they impact live systems. • Automation, Jobs & Crons • Architect database-level jobs, crons, and scheduled tasks for housekeeping, data validation, and performance checks. • Define best practices for automating materialized view refreshes, statistics updates, and data retention workflows. • Collaborate with DevOps teams to ensure cron scheduling aligns with system load and performance windows. • Introduce lightweight automation frameworks for periodic query performance audits and index efficiency checks. • Security, Transactions & Compliance • Define transaction isolation levels, locking strategies, and distributed transaction coordination for high-concurrency environments. • Collaborate with security and compliance teams to implement data encryption, access control, and auditing mechanisms. • Ensure database design and data storage align with compliance frameworks like DPDP, ISO 27001, or GDPR. • Validate schema and transaction logic to prevent data anomalies or concurrency violations. • Collaboration & Technical Leadership • Work closely with backend developers to architect high-performance queries, schema changes, and stored procedures. • Collaborate with DevOps and SRE teams to define HA/DR strategies, replication topologies, and capacity scaling (advisory role). • Mentor developers and junior database engineers in query optimization, data modeling, and performance diagnostics. • Participate in architecture reviews, technical design sessions, and sprint planning to guide database evolution across services. • Documentation & Knowledge Sharing • Maintain comprehensive documentation for schemas, views, triggers, crons, and CDC pipelines. • Record rationale for schema design choices, indexing decisions, and tuning recommendations. • Contribute to internal playbooks for query optimization, connection pooling best practices, and RCA workflows. • Drive knowledge sharing through internal workshops, design walkthroughs, and code review sessions.

Signals

Skill node-backend-developer
0.17
Alias
KRA data-engineer
0.62
Status: completed Created: 2026-06-09T21:29:20.574017Z Updated: 2026-06-12T11:54:04.256084Z API 3 duration: 13374 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

Database Architect

CASE NEW_CONSENSUS

slug: database-architect · id: — · source: llm

The primary skills indicate a strong focus on database management and architecture.

Resolution: human_review_required — role not in DB; role↔dimension links may be deferred.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped

Job description

Role Overview- Database Architect

We are looking for a highly skilled Database Architect with deep expertise in PostgreSQL to design, optimize, and scale our mission-critical data systems. The ideal candidate will work closely with development and operations teams to define data models, tune SQL queries, and architect high-performance, scalable database solutions. This role focuses on database design, optimization, and performance engineering, while actively collaborating with the operations team to recommend tuning strategies and resolve database bottlenecks across environments. Conversant with NoSQL databases is plus.

Key Responsibilities

• Database Architecture & Design
• Architect scalable, secure, and high-performance PostgreSQL database solutions for transactional and analytical systems.
• Design and maintain logical and physical schemas, ensuring proper normalization, entity relationships, and data integrity without compromising performance.
• Define database standards for naming conventions, indexing, constraints, partitioning, and query optimization.
• Architect and maintain database-specific materialized views, stored procedures, functions, and triggers.
• Oversee schema migrations, rollbacks, and version-controlled database evolution strategies.
• Implement distributed transaction management and ensure ACID compliance across services.
• Performance Optimization & Query Engineering
• Analyze and tune complex SQL queries, joins, and stored procedures for high-throughput applications.
• Define and monitor indexing strategies, query execution plans, and partitioning for large-scale datasets.
• Lead query optimization, deadlock detection, and resolution strategies with development teams.
• Collaborate with developers to optimize ORM configurations and reduce query overhead.
• Design database caching and sharding strategies that align with application access patterns.
• Review and recommend improvements for connection pooling configurations on the application side to ensure alignment with database capacity planning.
• Data Modelling, Integrity & CDC Integration
• Design conceptual, logical, and physical data models aligned with system requirements.
• Ensure data consistency and integrity using constraints, foreign keys, and triggers.
• Define and implement CDC (Change Data Capture) strategies using tools like Debezium for downstream synchronization and event-driven architectures.
• Collaborate with data engineering teams to define ETL and CDC-based data flows between microservices and analytics pipelines for data warehousing use cases.---
• Monitoring, Dashboards & Alerting
• Define and oversee database monitoring dashboards using tools like Prometheus, Grafana, or pgBadger.
• Set up alerting rules for query latency, replication lag, deadlocks, and transaction bottlenecks.
• Collaborate with operations teams to continuously improve observability, performance SLAs, and response metrics.
• Perform Root Cause Analysis (RCA) for P1 production issues caused by database performance or query inefficiencies.
• Conduct PostgreSQL log analysis to identify slow queries, locking patterns, and resource contention.
• Recommend design-level and query-level corrective actions based on production RCA findings.
• Regularly review metrics to anticipate and prevent scalability or resource utilization issues before they impact live systems.
• Automation, Jobs & Crons
• Architect database-level jobs, crons, and scheduled tasks for housekeeping, data validation, and performance checks.
• Define best practices for automating materialized view refreshes, statistics updates, and data retention workflows.
• Collaborate with DevOps teams to ensure cron scheduling aligns with system load and performance windows.
• Introduce lightweight automation frameworks for periodic query performance audits and index efficiency checks.
• Security, Transactions & Compliance
• Define transaction isolation levels, locking strategies, and distributed transaction coordination for high-concurrency environments.
• Collaborate with security and compliance teams to implement data encryption, access control, and auditing mechanisms.
• Ensure database design and data storage align with compliance frameworks like DPDP, ISO 27001, or GDPR.
• Validate schema and transaction logic to prevent data anomalies or concurrency violations.
• Collaboration & Technical Leadership
• Work closely with backend developers to architect high-performance queries, schema changes, and stored procedures.
• Collaborate with DevOps and SRE teams to define HA/DR strategies, replication topologies, and capacity scaling (advisory role).
• Mentor developers and junior database engineers in query optimization, data modeling, and performance diagnostics.
• Participate in architecture reviews, technical design sessions, and sprint planning to guide database evolution across services.
• Documentation & Knowledge Sharing
• Maintain comprehensive documentation for schemas, views, triggers, crons, and CDC pipelines.
• Record rationale for schema design choices, indexing decisions, and tuning recommendations.
• Contribute to internal playbooks for query optimization, connection pooling best practices, and RCA workflows.
• Drive knowledge sharing through internal workshops, design walkthroughs, and code review sessions.


Required Skills & Experience

• 8+ years of experience in database architecture, design, and performance engineering with PostgreSQL.
• Strong proficiency in SQL and PL/pgSQL, with proven ability to design performant, scalable database solutions.
• Expertise in query optimization, stored procedure design, indexing strategies, and execution plan analysis.
• Demonstrated experience in data modeling, normalization, and schema design for both transactional and analytical workloads.
• Hands-on experience in defining CDC architectures (e.g., Debezium) and data flow integration across microservices or analytics pipelines.
• Solid understanding of replication topologies, sharding, and partitioning from a design and scalability standpoint (advisory role, not operational).
• Experience working with connection pooling (PgBouncer, HikariCP, etc.) and ensuring capacity alignment between applications and database tiers.
• Proficiency in designing and monitoring database dashboards and alerts using tools such as Prometheus, Grafana, pgBadger, or PMM.
• Strong skills in diagnosing and resolving performance bottlenecks, deadlocks, and transactional anomalies.
• Experience with cloud database architectures (AWS RDS, Aurora PostgreSQL, Azure Database for PostgreSQL, GCP Cloud SQL).
• Proven ability to collaborate with developers, DevOps, and data engineering teams to build scalable and resilient data systems.
• Excellent communication and documentation skills, with the ability to articulate complex database concepts to technical and non-technical teams.


Good to Have

• Experience with NoSQL databases such as MongoDB administration.
• Exposure to Kafka, Airflow, or other ETL orchestration tools.
• Knowledge of containerized deployments (Kubernetes, Helm) and IaC tools (Terraform, Ansible).

Skills from this JD

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

PostgreSQL Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: PostgreSQL id=16 · postgresql

Aliases — catalog

  • PostgreSQL (CANONICAL) primary
  • PG 13 (VERSION)
  • PG 14 (VERSION)
  • PG 15 (VERSION)
  • PG 16 (VERSION)
  • PostgreSQL 13 (VERSION)
  • PostgreSQL 14 (VERSION)
  • PostgreSQL 15 (VERSION)
  • PostgreSQL 16 (VERSION)
  • Postgres 13 (VERSION)
  • Postgres 14 (VERSION)
  • Postgres 15 (VERSION)
  • Postgres 16 (VERSION)
  • pg10 (VERSION)
  • pg11 (VERSION)
  • pg12 (VERSION)
  • pg13 (VERSION)
  • pg14 (VERSION)
  • pg15 (VERSION)
  • pg16 (VERSION)
  • postgres (VERSION)
  • postgresql 10 (VERSION)
  • postgresql 11 (VERSION)
  • postgresql 12 (VERSION)
  • postgresql 13 (VERSION)
  • postgresql 14 (VERSION)
  • postgresql 15 (VERSION)
  • postgresql 16 (VERSION)
  • postgresql-16 (VERSION)
  • postgresql10 (VERSION)
  • postgresql11 (VERSION)
  • postgresql12 (VERSION)
  • postgresql13 (VERSION)
  • postgresql14 (VERSION)
  • postgresql15 (VERSION)
  • postgresql16 (VERSION)

Context tags (catalog)

ACID EXPLAIN JSONB PL/pgSQL PostGIS SQL VACUUM backup data integrity database migration extensions indexes indexing joins migration partitioning performance tuning pgAdmin query optimization replication schema stored procedures table partitioning transaction transactions triggers views

Stored enrichment (catalog DB)

Category
Datastore
Sub-category
Relational Database
Vendor
PostgreSQL Global Development Group
License
other_open
Year introduced
1996
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: PostgreSQL appears in a large share of backend/data engineering job postings and is a default managed option across AWS RDS, GCP Cloud SQL, and Azure Database, indicating broad hiring-pipeline adoption.

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)
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
ISO/IEC
License
unknown
Year introduced
1986
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: SQL is a hiring-pipeline staple across data, backend, and analytics roles; it appears in a very high volume of job descriptions and remains the standard query language for relational databases.

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)
NoSQL Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: NoSQL id=1346 · nosql

Aliases — catalog

  • NoSQL (CANONICAL)

Context tags (catalog)

CAP theorem Cassandra DynamoDB MongoDB Redis column-family data modeling document store eventual consistency graph database horizontal scaling key-value store query language schema-less sharding

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Database Paradigm
Confidence
0.93
Version strategy
NOT_APPLICABLE

Maturity reasoning: NoSQL is broadly listed in job descriptions across backend/data roles, with MongoDB, DynamoDB, and Cassandra appearing as common market signals; it remains a hiring-pipeline staple rather than a niche or sunset tech.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1019
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • NoSQL Databases Catalog dimension db id 19

    Library dimension (catalog)

    Roles linked in library: Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Materialized Views 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
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
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
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
ACID 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
ORM 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
Sharding 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
Connection Pooling Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: connection pooling id=53 · connection-pooling

Aliases — catalog

  • connection pooling (CANONICAL) primary

Context tags (catalog)

HikariCP JDBC ORM PgBouncer SQLAlchemy connection connection leak connection reuse connection string connection timeout data access layer database database connections database driver idle timeout load balancing max connections min connections performance pool pool exhaustion pool size resource management scalability session management thread-safe threading timeout transaction transaction management

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Resource Pooling Concept
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Connection pooling is a standard backend concept and appears routinely in JDs for Java, .NET, PostgreSQL, and cloud DB work; vendors like HikariCP, PgBouncer, and AWS RDS document it as a common production practice.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
2512
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Performance and Scalability Tuning Catalog dimension db id 11

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer, Python Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Change Data Capture Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Change data capture id=140 · change-data-capture

Aliases — catalog

  • Change data capture (CANONICAL) primary

Context tags (catalog)

Debezium ELT ETL Kafka Connect WAL binlog data pipeline event sourcing incremental load logical replication replication slot snapshotting streaming ingestion transaction log upsert

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Data Capture Methodology
Confidence
0.95
Version strategy
NOT_APPLICABLE

Maturity reasoning: CDC is broadly adopted in data engineering; it appears in many JDs for Kafka/Debezium/ETL roles and is a standard pattern for near-real-time replication and sync.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
102
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Batch Ingestion and Replication Catalog dimension db id 29

    Library dimension (catalog)

    Roles linked in library: Data Engineer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Batch Ingestion and Replication
batch-ingestion-and-replication
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Debezium 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
Data Engineering Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Microservices Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: microservices id=41 · microservices

Aliases — catalog

  • microservices (CANONICAL) primary

Context tags (catalog)

API Gateway API gateway CQRS DevOps Docker Kubernetes REST API RESTful services Saga pattern Spring Boot circuit breaker containerization decentralized distributed tracing domain-driven design event sourcing event-driven event-driven architecture gRPC load balancing message broker microservices patterns monitoring scalability service discovery service mesh

Stored enrichment (catalog DB)

Category
Architecture
Sub-category
Distributed System Architecture
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Microservices is a common architecture in job descriptions across backend/cloud roles, and major vendors like AWS, Google Cloud, and Kubernetes ecosystems provide first-class support and reference patterns.

Skill profile (library / DB)

Skill nature
PATTERN
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
1
Sub-category id
1
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Microservices and Distributed Systems Catalog dimension db id 9

    Library dimension (catalog)

    Roles linked in library: Backend Developer, Node.js Backend Developer, Scala Backend Developer

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
ETL 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
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Prometheus Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Prometheus id=46 · prometheus

Aliases — catalog

  • Prometheus (CANONICAL) primary

Context tags (catalog)

Alertmanager Grafana Kubernetes OpenMetrics PromQL Pushgateway TSDB Thanos alert rules alerts cAdvisor cloud-native container orchestration dashboards exporter kube-state-metrics labels metrics metrics endpoint metrics scraping monitoring node_exporter observability open-source pushgateway recording rules remote write scrape interval scraping service discovery time series visualization

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Monitoring Platform
Vendor
Cloud Native Computing Foundation
License
apache_2
Year introduced
2012
Confidence
0.62
Version strategy
NOT_APPLICABLE

Maturity reasoning: Prometheus is widely listed in DevOps/SRE job descriptions and is a standard CNCF monitoring stack component, often paired with Grafana for production observability.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
2837
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Backend Observability, Logging, and Diagnostics Catalog dimension db id 388

    Library dimension (catalog)

    Roles linked in library: Kotlin Backend Developer, Scala Backend Developer

  • Observability and Incident Response Catalog dimension db id 10

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer

  • Observability and Incident Triage Catalog dimension db id 155

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Observability and Operations Catalog dimension db id 143

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Operations
observability-and-operations
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Grafana Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Grafana id=47 · grafana

Aliases — catalog

  • Grafana (CANONICAL) primary

Context tags (catalog)

Alertmanager Grafana API Grafana Cloud Grafana Enterprise Grafana Loki Grafana Tempo Grafana plugins InfluxDB Kubernetes Loki Prometheus SLA SLO SRE Tempo alerting alerts annotations dashboard dashboarding dashboards data source data sources data visualization influxDB metrics monitoring observability plugins query editor templating time series time-series visualization

Stored enrichment (catalog DB)

Category
Platform
Sub-category
Observability Platform
Vendor
Grafana Labs
License
apache_2
Year introduced
2014
Confidence
0.90
Version strategy
NOT_APPLICABLE

Maturity reasoning: Grafana appears in many DevOps/SRE job descriptions and is a standard observability dashboarding tool alongside Prometheus and Loki; strong GitHub/community adoption and broad vendor integrations signal mainstream use.

Skill profile (library / DB)

Skill nature
PLATFORM
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
9
Sub-category id
176
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Backend Observability, Logging, and Diagnostics Catalog dimension db id 388

    Library dimension (catalog)

    Roles linked in library: Kotlin Backend Developer, Scala Backend Developer

  • Observability and Incident Response Catalog dimension db id 10

    Library dimension (catalog)

    Roles linked in library: .NET Backend Developer, Backend Developer, Node.js Backend Developer, PHP Backend Developer

  • Observability and Incident Triage Catalog dimension db id 155

    Library dimension (catalog)

    Roles linked in library: DevOps Engineer

  • Observability and Operations Catalog dimension db id 143

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Observability and Operations
observability-and-operations
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
pgBadger 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
Monitoring Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Cron 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
Infrastructure Tools
Sub-category
general
Skill nature
TOOL
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Data Encryption 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
Security Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Access Control 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
Security Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Version strategy
UNVERSIONED
Auditing 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
Security Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
ISO 27001 Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: ISO 27001 id=399 · iso-27001

Aliases — catalog

  • ISO 27001 (VERSION)
  • ISO 27001:2013 (VERSION)
  • ISO 27001:2022 (VERSION)
  • ISO/IEC 27001 2013 (VERSION)
  • ISO/IEC 27001 2022 (VERSION)
  • ISO/IEC 27001:2013 (VERSION)
  • ISO/IEC 27001:2022 (VERSION)

Context tags (catalog)

Annex A GDPR ISMS PDCA Statement of Applicability access control asset inventory asset management audit business continuity certification certification audit compliance continuous improvement control objectives controls corrective action data protection external audit incident management information security information security management internal audit management review policy development risk assessment security controls security framework security policies stakeholder engagement supplier management supplier risk threat analysis vulnerability assessment

Stored enrichment (catalog DB)

Category
Standard
Sub-category
Information Security Standard
Vendor
International Organization for Standardization (ISO)
Year introduced
2005
Confidence
0.99
Version strategy
SEPARATE_ENTITY
Version tag
2022

Maturity reasoning: Commonly requested in security/compliance job descriptions and vendor procurement requirements; many orgs list ISO 27001 certification as a baseline control framework for audits and third-party risk.

Skill profile (library / DB)

Skill nature
STANDARD
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
12
Sub-category id
275
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Cloud Security Governance Catalog dimension db id 138

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

  • Compliance and Security Frameworks Catalog dimension db id 73

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Standards, Protocols & Compliance Catalog dimension db id 452

    Library dimension (catalog)

    Roles linked in library: Engineering Manager, Sitecore Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Cloud Security Governance
cloud-security-governance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Compliance and Security Frameworks
compliance-and-security-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GDPR Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: GDPR id=402 · gdpr

Aliases — catalog

  • GDPR (CANONICAL) primary

Context tags (catalog)

DPA DPIA DPO RoPA SCCs accountability audit trail compliance consent consent management controller cross-border transfers data breach data breach notification data minimization data portability data privacy data processing data processing agreement data protection data protection officer data subject data subject rights encryption lawful basis personal data privacy by design privacy impact assessment privacy policy processor records of processing regulatory framework right to access right to erasure third-party vendors

Stored enrichment (catalog DB)

Category
Standard
Sub-category
Privacy Regulation Standard
Vendor
European Union
Year introduced
2016
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: GDPR is a widely cited compliance requirement in job postings for product, legal, security, and data roles across EU-facing companies; it remains an active regulatory standard rather than a niche tool.

Skill profile (library / DB)

Skill nature
STANDARD
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
12
Sub-category id
3215
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Compliance and Security Frameworks Catalog dimension db id 73

    Library dimension (catalog)

    Roles linked in library: Cloud Security Engineer, Cyber Security Engineer

  • Standards, Protocols & Compliance Catalog dimension db id 452

    Library dimension (catalog)

    Roles linked in library: Engineering Manager, Sitecore Dev

  • Web Standards & Compliance Catalog dimension db id 343

    Library dimension (catalog)

    Roles linked in library: WordPress Dev

  • Web Standards, Protocols & Compliance Catalog dimension db id 436

    Library dimension (catalog)

    Roles linked in library: Shopify Dev

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Compliance and Security Frameworks
compliance-and-security-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Standards & Compliance
web-standards-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Web Standards, Protocols & Compliance
web-standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
DPDP 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
Security Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
FAST
Typical lifespan
SHORT_LIVED
Version strategy
VERSIONED
High Availability Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: high availability id=764 · high-availability

Aliases — catalog

  • high availability (CANONICAL) primary

Context tags (catalog)

RPO RTO SLA active-active active-passive clustering disaster recovery failover fault tolerance heartbeat load balancing redundancy replication rolling upgrade zero downtime

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Reliability Concept
Confidence
0.92
Version strategy
NOT_APPLICABLE

Maturity reasoning: High availability is a standard requirement in cloud/SRE job descriptions and vendor docs; AWS, Azure, and GCP all publish HA reference architectures, showing broad market adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
535
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Availability and Disaster Recovery Catalog dimension db id 141

    Library dimension (catalog)

    Roles linked in library: Cloud Architect

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Availability and Disaster Recovery
availability-and-disaster-recovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Disaster Recovery 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
Infrastructure Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Replication 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
Databases
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Code Review Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Code Review id=516 · code-review

Aliases — catalog

  • Code Review (CANONICAL)

Context tags (catalog)

Bitbucket GitHub GitLab PR review approval workflow branch protection code quality diff inline comments linting merge request pair programming pull request review checklist static analysis

Stored enrichment (catalog DB)

Category
SoftSkill
Sub-category
Code Review
Confidence
0.96
Version strategy
NOT_APPLICABLE

Maturity reasoning: Code review is a standard hiring-pipeline requirement in engineering JDs and is built into major platforms like GitHub/GitLab pull-request workflows, indicating broad adoption.

Skill profile (library / DB)

Skill nature
PRACTICE
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
58
Sub-category id
364
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)
Agile Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Agile id=520 · agile

Aliases — catalog

  • Agile (CANONICAL) primary

Context tags (catalog)

Kanban SAFe Scrum backlog backlog grooming burndown burndown chart continuous delivery continuous improvement cross-functional daily standup epics incremental development iteration iteration planning lean product backlog product owner retrospective sprint sprint planning stand-up story points user stories velocity

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Agile
Confidence
0.99
Version strategy
NOT_APPLICABLE

Maturity reasoning: Agile appears in a large share of software job descriptions and is a standard hiring-pipeline requirement; Scrum/Kanban are commonly listed alongside it, showing broad market adoption.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3594
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

  • Software Concepts, Patterns & Practices Catalog dimension db id 478

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

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)
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sprint Planning Secondary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: sprint planning id=4550 · sprint-planning

Aliases — catalog

  • sprint planning (CANONICAL) primary

Context tags (catalog)

agile framework backlog refinement burndown chart cross-functional team definition of done incremental delivery iteration planning retrospective scrum ceremonies sprint goals stakeholder engagement task estimation timeboxing user stories velocity tracking

Stored enrichment (catalog DB)

Category
Methodology
Sub-category
Sprint Planning
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Sprint planning is a standard Scrum ceremony and appears routinely in Agile job descriptions; it’s a hiring-pipeline staple for product and engineering teams.

Skill profile (library / DB)

Skill nature
METHODOLOGY
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
8
Sub-category id
3628
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • Delivery Planning and Execution Catalog dimension db id 461

    Library dimension (catalog)

    Roles linked in library: Engineering Manager

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
Delivery Planning and Execution
delivery-planning-and-execution
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

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
PostgreSQL in_db
Relational Data Modeling
relational-data-modeling
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL in_db
Relational Database Design
relational-database-design
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
PostgreSQL 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)
NoSQL in_db
NoSQL Databases
nosql-databases
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Connection Pooling in_db
Performance and Scalability Tuning
performance-and-scalability-tuning
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Change Data Capture in_db
Batch Ingestion and Replication
batch-ingestion-and-replication
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Microservices in_db
Microservices and Distributed Systems
microservices-and-distributed-systems
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Prometheus in_db
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Prometheus in_db
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Prometheus in_db
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Prometheus in_db
Observability and Operations
observability-and-operations
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Grafana in_db
Backend Observability, Logging, and Diagnostics
backend-observability-logging-and-diagnostics
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Grafana in_db
Observability and Incident Response
observability-and-incident-response
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Grafana in_db
Observability and Incident Triage
observability-and-incident-triage
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Grafana in_db
Observability and Operations
observability-and-operations
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
ISO 27001 in_db
Cloud Security Governance
cloud-security-governance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
ISO 27001 in_db
Compliance and Security Frameworks
compliance-and-security-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
ISO 27001 in_db
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GDPR in_db
Compliance and Security Frameworks
compliance-and-security-frameworks
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GDPR in_db
Standards, Protocols & Compliance
standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GDPR in_db
Web Standards & Compliance
web-standards-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
GDPR in_db
Web Standards, Protocols & Compliance
web-standards-protocols-compliance
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
High Availability in_db
Availability and Disaster Recovery
availability-and-disaster-recovery
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Code Review in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Agile in_db
Software Concepts, Patterns & Practices
software-concepts-patterns-practices
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Sprint Planning in_db
Delivery Planning and Execution
delivery-planning-and-execution
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Materialized Views | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Stored Procedures | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Functions | 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 ACID | type=Databases subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed ORM | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Sharding | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
canonical_skill_proposed Debezium | type=Data Engineering Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed ETL | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed pgBadger | type=Monitoring Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Cron | type=Infrastructure Tools subtype=general nature=TOOL lifespan=MULTI_YEAR
canonical_skill_proposed Data Encryption | type=Security Tools subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Access Control | type=Security Tools subtype=general nature=CONCEPT lifespan=EVERGREEN
canonical_skill_proposed Auditing | type=Security Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed DPDP | type=Security Tools subtype=general nature=CONCEPT lifespan=SHORT_LIVED
canonical_skill_proposed Disaster Recovery | type=Infrastructure Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Replication | type=Databases subtype=general nature=CONCEPT lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleDatabase Architect
Experience8+ years of experience in database architecture, design, and performance engineering with PostgreSQL.
DomainSoftware & SaaS Products
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": null,
  "ai_kras": [],
  "certifications": [],
  "company_name": null,
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [],
      "domain": "Software \u0026 SaaS Products"
    },
    "secondary": null
  },
  "education": [],
  "experience": {
    "max": null,
    "min": 8,
    "raw": "8+ years of experience in database architecture, design, and performance engineering with PostgreSQL."
  },
  "job_locations": [],
  "role": "Database Architect",
  "role_aliases": [
    {
      "name": "Database Engineer",
      "reasoning": "common industry alt for the same archetype",
      "relation": "synonym"
    },
    {
      "name": "Data Architect",
      "reasoning": "JD emphasizes data modeling and architecture",
      "relation": "adjacent"
    }
  ],
  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
    {
      "bullet_count": 0,
      "heading": "Role Overview",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "We are looking for a",
        "last_5_words": "is plus."
      },
      "text": "We are looking for a highly skilled Database Architect with deep expertise in PostgreSQL to design, optimize, and scale our mission-critical data systems. The ideal candidate will work closely with development and operations teams to define data models, tune SQL queries, and architect high-performance, scalable database solutions. This role focuses on database design, optimization, and performance engineering, while actively collaborating with the operations team to recommend tuning strategies and resolve database bottlenecks across environments. Conversant with NoSQL databases is plus.",
      "word_count": 83
    },
    {
      "bullet_count": 40,
      "heading": "Key Responsibilities",
      "heading_was_present": true,
      "source_marker": {
        "first_5_words": "\u2022 Database Architecture \u0026 Design\n\u2022",
        "last_5_words": "and code review sessions."
      },
      "text": "\u2022 Database Architecture \u0026 Design\n\u2022 Architect scalable, secure, and high-performance PostgreSQL database solutions for transactional and analytical systems.\n\u2022 Design and maintain logical and physical schemas, ensuring proper normalization, entity relationships, and data integrity without compromising performance.\n\u2022 Define database standards for naming conventions, indexing, constraints, partitioning, and query optimization.\n\u2022 Architect and maintain database-specific materialized views, stored procedures, functions, and triggers.\n\u2022 Oversee schema migrations, rollbacks, and version-controlled database evolution strategies.\n\u2022 Implement distributed transaction management and ensure ACID compliance across services.\n\u2022 Performance Optimization \u0026 Query Engineering\n\u2022 Analyze and tune complex SQL queries, joins, and stored procedures for high-throughput applications.\n\u2022 Define and monitor indexing strategies, query execution plans, and partitioning for large-scale datasets.\n\u2022 Lead query optimization, deadlock detection, and resolution strategies with development teams.\n\u2022 Collaborate with developers to optimize ORM configurations and reduce query overhead.\n\u2022 Design database caching and sharding strategies that align with application access patterns.\n\u2022 Review and recommend improvements for connection pooling configurations on the application side to ensure alignment with database capacity planning.\n\u2022 Data Modelling, Integrity \u0026 CDC Integration\n\u2022 Design conceptual, logical, and physical data models aligned with system requirements.\n\u2022 Ensure data consistency and integrity using constraints, foreign keys, and triggers.\n\u2022 Define and implement CDC (Change Data Capture) strategies using tools like Debezium for downstream synchronization and event-driven architectures.\n\u2022 Collaborate with data engineering teams to define ETL and CDC-based data flows between microservices and analytics pipelines for data warehousing use cases.\n\u2022 Monitoring, Dashboards \u0026 Alerting\n\u2022 Define and oversee database monitoring dashboards using tools like Prometheus, Grafana, or pgBadger.\n\u2022 Set up alerting rules for query latency, replication lag, deadlocks, and transaction bottlenecks.\n\u2022 Collaborate with operations teams to continuously improve observability, performance SLAs, and response metrics.\n\u2022 Perform Root Cause Analysis (RCA) for P1 production issues caused by database performance or query inefficiencies.\n\u2022 Conduct PostgreSQL log analysis to identify slow queries, locking patterns, and resource contention.\n\u2022 Recommend design-level and query-level corrective actions based on production RCA findings.\n\u2022 Regularly review metrics to anticipate and prevent scalability or resource utilization issues before they impact live systems.\n\u2022 Automation, Jobs \u0026 Crons\n\u2022 Architect database-level jobs, crons, and scheduled tasks for housekeeping, data validation, and performance checks.\n\u2022 Define best practices for automating materialized view refreshes, statistics updates, and data retention workflows.\n\u2022 Collaborate with DevOps teams to ensure cron scheduling aligns with system load and performance windows.\n\u2022 Introduce lightweight automation frameworks for periodic query performance audits and index efficiency checks.\n\u2022 Security, Transactions \u0026 Compliance\n\u2022 Define transaction isolation levels, locking strategies, and distributed transaction coordination for high-concurrency environments.\n\u2022 Collaborate with security and compliance teams to implement data encryption, access control, and auditing mechanisms.\n\u2022 Ensure database design and data storage align with compliance frameworks like DPDP, ISO 27001, or GDPR.\n\u2022 Validate schema and transaction logic to prevent data anomalies or concurrency violations.\n\u2022 Collaboration \u0026 Technical Leadership\n\u2022 Work closely with backend developers to architect high-performance queries, schema changes, and stored procedures.\n\u2022 Collaborate with DevOps and SRE teams to define HA/DR strategies, replication topologies, and capacity scaling (advisory role).\n\u2022 Mentor developers and junior database engineers in query optimization, data modeling, and performance diagnostics.\n\u2022 Participate in architecture reviews, technical design sessions, and sprint planning to guide database evolution across services.\n\u2022 Documentation \u0026 Knowledge Sharing\n\u2022 Maintain comprehensive documentation for schemas, views, triggers, crons, and CDC pipelines.\n\u2022 Record rationale for schema design choices, indexing decisions, and tuning recommendations.\n\u2022 Contribute to internal playbooks for query optimization, connection pooling best practices, and RCA workflows.\n\u2022 Drive knowledge sharing through internal workshops, design walkthroughs, and code review sessions.",
      "word_count": 1035
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "PostgreSQL"
    },
    {
      "is_primary": true,
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        "display_name": "Code Review",
        "id": 516,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "PRACTICE",
        "slug": "code-review",
        "sub_category_id": 364,
        "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": "Code Review",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Code Review",
      "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": "Agile",
          "alias_type": "CANONICAL",
          "id": 868,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "Agile",
        "id": 520,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "agile",
        "sub_category_id": 3594,
        "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": "Agile",
          "llm_role": null,
          "roles_from_db": []
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Software Concepts, Patterns \u0026 Practices",
            "id": 478,
            "rationale": "Champion foundational software design patterns, development methodologies, and engineering best practices.",
            "slug": "software-concepts-patterns-practices",
            "source": "db"
          },
          "input_skill": "Agile",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Agile",
      "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": "sprint planning",
          "alias_type": "CANONICAL",
          "id": 6399,
          "is_primary": true,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 8,
        "display_name": "sprint planning",
        "id": 4550,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "METHODOLOGY",
        "slug": "sprint-planning",
        "sub_category_id": 3628,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "Delivery Planning and Execution",
            "id": 461,
            "rationale": "Coordinates how work gets done across the team, including sequencing, commitments, dependencies, and follow-through. This cluster is coherent because EMs are accountable for predictable delivery rather than the technical implementation itself.",
            "slug": "delivery-planning-and-execution",
            "source": "db"
          },
          "input_skill": "Sprint Planning",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "Engineering Manager",
              "id": 121,
              "rationale": null,
              "role_archetype": null,
              "slug": "engineering-manager",
              "source": "db"
            }
          ]
        }
      ],
      "input_skill": "Sprint Planning",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Materialized Views",
    "Stored Procedures",
    "Functions",
    "Triggers",
    "ACID",
    "ORM",
    "Sharding",
    "Debezium",
    "ETL",
    "pgBadger",
    "Cron",
    "Data Encryption",
    "Access Control",
    "Auditing",
    "DPDP",
    "Disaster Recovery",
    "Replication"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Database Architect",
    "id": null,
    "rationale": "The primary skills indicate a strong focus on database management and architecture.",
    "role_archetype": "Engineering role focused on the design and management of database systems.",
    "slug": "database-architect",
    "source": "llm"
  },
  "chosen_role_resolution": "human_review_required",
  "final_input_skills": [
    {
      "skill": "PostgreSQL",
      "tag": "in_db"
    },
    {
      "skill": "SQL",
      "tag": "in_db"
    },
    {
      "skill": "NoSQL",
      "tag": "in_db"
    },
    {
      "skill": "Materialized Views",
      "tag": "new"
    },
    {
      "skill": "Stored Procedures",
      "tag": "new"
    },
    {
      "skill": "Functions",
      "tag": "new"
    },
    {
      "skill": "Triggers",
      "tag": "new"
    },
    {
      "skill": "ACID",
      "tag": "new"
    },
    {
      "skill": "ORM",
      "tag": "new"
    },
    {
      "skill": "Sharding",
      "tag": "new"
    },
    {
      "skill": "Connection Pooling",
      "tag": "in_db"
    },
    {
      "skill": "Change Data Capture",
      "tag": "in_db"
    },
    {
      "skill": "Debezium",
      "tag": "new"
    },
    {
      "skill": "Microservices",
      "tag": "in_db"
    },
    {
      "skill": "ETL",
      "tag": "new"
    },
    {
      "skill": "Prometheus",
      "tag": "in_db"
    },
    {
      "skill": "Grafana",
      "tag": "in_db"
    },
    {
      "skill": "pgBadger",
      "tag": "new"
    },
    {
      "skill": "Cron",
      "tag": "new"
    },
    {
      "skill": "Data Encryption",
      "tag": "new"
    },
    {
      "skill": "Access Control",
      "tag": "new"
    },
    {
      "skill": "Auditing",
      "tag": "new"
    },
    {
      "skill": "ISO 27001",
      "tag": "in_db"
    },
    {
      "skill": "GDPR",
      "tag": "in_db"
    },
    {
      "skill": "DPDP",
      "tag": "new"
    },
    {
      "skill": "High Availability",
      "tag": "in_db"
    },
    {
      "skill": "Disaster Recovery",
      "tag": "new"
    },
    {
      "skill": "Replication",
      "tag": "new"
    },
    {
      "skill": "Code Review",
      "tag": "in_db"
    },
    {
      "skill": "Agile",
      "tag": "in_db"
    },
    {
      "skill": "Sprint Planning",
      "tag": "in_db"
    }
  ],
  "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": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "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"
        },
        "dimension_id": 216,
        "input_skill": "PostgreSQL",
        "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": "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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 16,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "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": "PostgreSQL",
        "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": ".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"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 16,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "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"
        },
        "dimension_id": 371,
        "input_skill": "PostgreSQL",
        "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": "Go Backend Developer",
            "id": 81,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "go-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 16,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "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"
        },
        "dimension_id": 267,
        "input_skill": "SQL",
        "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": "Pega Developer",
            "id": 24,
            "rationale": null,
            "role_archetype": null,
            "slug": "pega-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "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"
        },
        "dimension_id": 475,
        "input_skill": "SQL",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "Engineering Manager",
            "id": 121,
            "rationale": null,
            "role_archetype": null,
            "slug": "engineering-manager",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "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"
        },
        "dimension_id": 21,
        "input_skill": "SQL",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 101,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "NoSQL Databases",
          "id": 19,
          "rationale": "Models and manages data using non-relational database systems.",
          "slug": "nosql-databases",
          "source": "db"
        },
        "dimension_id": 19,
        "input_skill": "NoSQL",
        "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": 1346,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Performance and Scalability Tuning",
          "id": 11,
          "rationale": "Techniques for improving throughput, latency, and resource efficiency in PHP backend services. This includes profiling, query optimization, concurrency limits, memory use, and bottleneck analysis.",
          "slug": "performance-and-scalability-tuning",
          "source": "db"
        },
        "dimension_id": 11,
        "input_skill": "Connection Pooling",
        "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": ".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": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "PHP Backend Developer",
            "id": 86,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "php-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Python Backend Developer",
            "id": 80,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "python-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 53,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Batch Ingestion and Replication",
          "id": 29,
          "rationale": "Moving data from source systems into landing zones or warehouses on batch schedules. Covers file ingestion, CDC-style replication, incremental loads, and source-to-target synchronization.",
          "slug": "batch-ingestion-and-replication",
          "source": "db"
        },
        "dimension_id": 29,
        "input_skill": "Change Data Capture",
        "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": "Data Engineer",
            "id": 2,
            "rationale": null,
            "role_archetype": null,
            "slug": "data-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 140,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Microservices and Distributed Systems",
          "id": 9,
          "rationale": "Architectural patterns for decomposed backend systems and the operational concerns they introduce. Covers service boundaries, consistency tradeoffs, retries, circuit breakers, and distributed coordination.",
          "slug": "microservices-and-distributed-systems",
          "source": "db"
        },
        "dimension_id": 9,
        "input_skill": "Microservices",
        "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"
          },
          {
            "display_name": "Node.js Backend Developer",
            "id": 82,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "node-backend-developer",
            "source": "db"
          },
          {
            "display_name": "Scala Backend Developer",
            "id": 87,
            "rationale": null,
            "role_archetype": "Engineering",
            "slug": "scala-backend-developer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 41,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": null,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "Backend Observability, Logging, and Diagnostics",
          "id": 388,
          "rationale": "Instrumentation and troubleshooting practices used to understand and improve backend service behavior in production and lower environments. This includes logs, metrics, traces, alerting, dashboards, structured logging, distributed tracing, health checks, and root-cause analysis using ecosystem-specific tools such as SLF4J, Logback, Micrometer, OpenTelemetry, Prometheus, Grafana, ILogger, Serilog, and Application Insights.",
          "slug": "backend-observability-logging-and-diagnostics",
          "source": "db"
        },
        "dimension_id": 388,
        "input_skill": "Prometheus",
        "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,
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  },
  "planner_output": null,
  "run_id": "3b41bee4-2730-47e1-845b-e5658db78eac"
}

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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