PSR Modeler Offshore
Prodapt Solutions · Chennai · onsite · Posted 72d ago
Undisclosed10–15 yrsfulltimeSourced from
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About this role
Overview
Responsibilities
Requirements
The PSR SME owns the design and delivery of the Product Service Record data model the authoritative representation of how CUSTOMER''s network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.
Key Responsibilities
PSR Model Design
- Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
- Define PSR entities, attributes, relationships, and hierarchies.
- Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
- Validate model against current Catalog, Inventory and Ordering systems.
Source System Analysis
- Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
- Map data lineage from source systems to PSR model.
- Raise structured data requests to CUSTOMER stakeholders.
Stakeholder Workshop Engagement
- Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
- Align with CMDB SME on CI-to-product mapping.
- Present findings and model designs to programme leadership.
Use Case Enablement
- Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
- Support event correlation and service impact design.
Programme Delivery
- Author workstream deliverables; maintain RAID log.
- Contribute to JIRA stories and sprint planning.
Ensure delivery aligns to PI features and sprint goals.
Key Deliverables
1Generic PSR Data Model
Product-agnostic entities, attributes relationships.
2CUSTOMER-Specific PSR Models
Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data.
3PSR Attribute Specification Sheet
Attribute detail: type, source, transformation rule, mandatory flag.
4Source System Analysis Report
Current Catalog, Inventory and Ordering systems schemas, gaps, quality findings.
5Data Lineage Map (PSR)
Source-to-PSR traceability for all key data attributes.
6PSRCMDB Integration Design
How PSR entities map to CMDB CI classes.
7Use Case Data Requirements
Data needs per AI Ops use case at each delivery layer.
8Gap Analysis Recommendations
Current state vs. PSR model requirements with prioritised actions.
9PSR Workstream RAID Log
Ongoing risks, assumptions, issues, and dependencies.
Skills Experience
Domain Knowledge
- Telecom product service structures (MPLS, IP Connect, SD-WAN).
- Product catalogue and service inventory data models in a telco OSS/BSS context.
- Network provisioning and fulfilment systems (billing gateways, order management).
- CMDB data models and CI class design ServiceNow preferred.
- AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
- Service assurance and fault management in network operations.
Technical Skills
- Data modelling entity-relationship, conceptual, logical, physical.
- SQL / database querying for schema analysis and validation.
- Data mapping and transformation specification writing.
- Ability to read and interpret complex, under documented database schemas.
- JIRA user story creation and sprint tracking.
- TMF SID certification - desirable
- ServiceNow (ITSM, CMDB, Event Management) desirable.
- Kafka / event streaming awareness desirable.
Behavioural Consulting
- Stakeholder engagement extracting requirements from time-poor CUSTOMER SMEs.
- Structured problem-solving in data-poor, ambiguous environments.
- Persistence in accessing and validating data from complex legacy systems.
- Clear communication presenting data models to technical and non-technical audiences.
- Proactive risk identification and escalation.
Comfortable with iterative, agile delivery and progressive elaboration.
Responsibilities
The PSR SME owns the design and delivery of the Product Service Record data model the authoritative representation of how CUSTOMER''s network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.
Key Responsibilities
PSR Model Design
- Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
- Define PSR entities, attributes, relationships, and hierarchies.
- Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
- Validate model against current Catalog, Inventory and Ordering systems.
Source System Analysis
- Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
- Map data lineage from source systems to PSR model.
- Raise structured data requests to CUSTOMER stakeholders.
Stakeholder Workshop Engagement
- Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
- Align with CMDB SME on CI-to-product mapping.
- Present findings and model designs to programme leadership.
Use Case Enablement
- Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
- Support event correlation and service impact design.
Programme Delivery
- Author workstream deliverables; maintain RAID log.
- Contribute to JIRA stories and sprint planning.
Ensure delivery aligns to PI features and sprint goals.
Key Deliverables
1Generic PSR Data Model
Product-agnostic entities, attributes relationships.
2CUSTOMER-Specific PSR Models
Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data.
3PSR Attribute Specification Sheet
Attribute detail: type, source, transformation rule, mandatory flag.
4Source System Analysis Report
Current Catalog, Inventory and Ordering systems schemas, gaps, quality findings.
5Data Lineage Map (PSR)
Source-to-PSR traceability for all key data attributes.
6PSRCMDB Integration Design
How PSR entities map to CMDB CI classes.
7Use Case Data Requirements
Data needs per AI Ops use case at each delivery layer.
8Gap Analysis Recommendations
Current state vs. PSR model requirements with prioritised actions.
9PSR Workstream RAID Log
Ongoing risks, assumptions, issues, and dependencies.
Skills Experience
Domain Knowledge
- Telecom product service structures (MPLS, IP Connect, SD-WAN).
- Product catalogue and service inventory data models in a telco OSS/BSS context.
- Network provisioning and fulfilment systems (billing gateways, order management).
- CMDB data models and CI class design ServiceNow preferred.
- AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
- Service assurance and fault management in network operations.
Technical Skills
- Data modelling entity-relationship, conceptual, logical, physical.
- SQL / database querying for schema analysis and validation.
- Data mapping and transformation specification writing.
- Ability to read and interpret complex, under documented database schemas.
- JIRA user story creation and sprint tracking.
- TMF SID certification - desirable
- ServiceNow (ITSM, CMDB, Event Management) desirable.
- Kafka / event streaming awareness desirable.
Behavioural Consulting
- Stakeholder engagement extracting requirements from time-poor CUSTOMER SMEs.
- Structured problem-solving in data-poor, ambiguous environments.
- Persistence in accessing and validating data from complex legacy systems.
- Clear communication presenting data models to technical and non-technical audiences.
- Proactive risk identification and escalation.
Comfortable with iterative, agile delivery and progressive elaboration.
Requirements
The PSR SME owns the design and delivery of the Product Service Record data model the authoritative representation of how CUSTOMER''s network products are structured and related to underlying infrastructure. The model underpins AI-driven event correlation, anomaly detection, root cause analysis, and service impact assessment across the AI Ops platform.
Key Responsibilities
PSR Model Design
- Design end-to-end PSR data model for in-scope products (IP Connect, MPLS, SD-WAN).
- Define PSR entities, attributes, relationships, and hierarchies.
- Develop generic model first; iterate to CUSTOMER-specific as data is confirmed.
- Validate model against current Catalog, Inventory and Ordering systems.
Source System Analysis
- Analyse current Catalog, Inventory and Ordering systems for schemas, structures, and gaps.
- Map data lineage from source systems to PSR model.
- Raise structured data requests to CUSTOMER stakeholders.
Stakeholder Workshop Engagement
- Lead PSR discovery workshops with CUSTOMER product and provisioning teams.
- Align with CMDB SME on CI-to-product mapping.
- Present findings and model designs to programme leadership.
Use Case Enablement
- Define data requirements per AI Ops use case across ingest, enrich, correlate, and present layers.
- Support event correlation and service impact design.
Programme Delivery
- Author workstream deliverables; maintain RAID log.
- Contribute to JIRA stories and sprint planning.
Ensure delivery aligns to PI features and sprint goals.
Key Deliverables
1Generic PSR Data Model
Product-agnostic entities, attributes relationships.
2CUSTOMER-Specific PSR Models
Per-product models (IP Connect, MPLS, SD-WAN) validated against CUSTOMER data.
3PSR Attribute Specification Sheet
Attribute detail: type, source, transformation rule, mandatory flag.
4Source System Analysis Report
Current Catalog, Inventory and Ordering systems schemas, gaps, quality findings.
5Data Lineage Map (PSR)
Source-to-PSR traceability for all key data attributes.
6PSRCMDB Integration Design
How PSR entities map to CMDB CI classes.
7Use Case Data Requirements
Data needs per AI Ops use case at each delivery layer.
8Gap Analysis Recommendations
Current state vs. PSR model requirements with prioritised actions.
9PSR Workstream RAID Log
Ongoing risks, assumptions, issues, and dependencies.
Skills Experience
Domain Knowledge
- Telecom product service structures (MPLS, IP Connect, SD-WAN).
- Product catalogue and service inventory data models in a telco OSS/BSS context.
- Network provisioning and fulfilment systems (billing gateways, order management).
- CMDB data models and CI class design ServiceNow preferred.
- AI Ops concepts: event correlation, anomaly detection, service impact, root cause analysis.
- Service assurance and fault management in network operations.
Technical Skills
- Data modelling entity-relationship, conceptual, logical, physical.
- SQL / database querying for schema analysis and validation.
- Data mapping and transformation specification writing.
- Ability to read and interpret complex, under documented database schemas.
- JIRA user story creation and sprint tracking.
- TMF SID certification - desirable
- ServiceNow (ITSM, CMDB, Event Management) desirable.
- Kafka / event streaming awareness desirable.
Behavioural Consulting
- Stakeholder engagement extracting requirements from time-poor CUSTOMER SMEs.
- Structured problem-solving in data-poor, ambiguous environments.
- Persistence in accessing and validating data from complex legacy systems.
- Clear communication presenting data models to technical and non-technical audiences.
- Proactive risk identification and escalation.
Comfortable with iterative, agile delivery and progressive elaboration.
Sourced from naukri
Skills
itsmAgileData lineageApache KafkaFault Managementgap analysismodelerCMDBcorrelationdata mappingDatabase QueryingAgile DeliveryMappingdata modelsAnomaly DetectionImpact AssessmentJira AtlassianMPLSEvent ManagementArtificial Intelligence
About Prodapt
Prodapt Solutions
IT Services & Consulting
3.0k+
employees
1999
27 years old
Chennai, Tamil Nadu
India
About
Prodapt Solutions specializes in connected technology services, supporting telecom operators and digital service providers in optimizing their networking capabilities.
Industries
IT Services & ConsultingTelecom
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3.5/ 5
Culture
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Career growth
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Work-life
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