Investment Data Analyst
for section headings, - for lists,
for prose.
We need to preserve all substantive information; do not invent or summarize away detail. Must not omit details.
We need to decide which sections to include: About the role (intro), Responsibilities, Requirements (maybe combine Technical Requirements and Preferred Qualifications?), Qualifications (maybe separate?), Skills (maybe technical skills?), Schedule.
But we must not create thin sections. Prefer few substantive sections.
We could have sections: About the role (intro paragraph), Responsibilities (list), Requirements (list), Schedule (p). Possibly also Qualifications (but could merge with Requirements). The posting has "Technical Requirements And Experience" and "Preferred Qualifications". Also "Success in This Role" and "Role Summary". Could combine into About the role.
We need to ensure we don't leave empty sections.
Let's extract substantive content:
Intro: "As a team member in Finance at Nationwide, a Fortune 100 company with nearly $70 billion in annual sales, the opportunities are endless! Let Nationwide help create your career journey! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care. The Investment Data Management professional supporting Data Insights will translate investment-business needs into reliable, governed data products and business intelligence solutions. This position combines business partnership with hands-on technical delivery across cloud data platforms, data models, reporting tools, and emerging artificial intelligence capabilities."
That's about the role.
Responsibilities: There's a big list under "Key Responsibilities Include" and later "Job Description Key Responsibilities:" which seems to repeat or expand. We need to preserve all, not duplicate? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." If there are duplicates, we might need to include them? It says remove duplicated lines. So we should deduplicate.
We need to combine responsibilities from both sections, removing duplicates.
Let's list responsibilities from first "Key Responsibilities Include":
- Designs, develops, and maintains data models, curated datasets, semantic models, and data products that support investment reporting, analytics, operational processes, and self-service business intelligence.
- Builds, supports, and troubleshoots data pipelines, dataflows, notebooks, jobs, scheduled processes, and related integrations; investigates failures, identifies root causes, and coordinates timely remediation.
- Uses data modeling principles to define relationships, business rules, transformations, keys, hierarchies, measures, and other structures needed to create consistent and reusable data products.
- Creates and maintains Business Objects universes, reports, scheduled distributions, and related reporting components, while supporting the transition of legacy reporting capabilities to modern, governed solutions where appropriate.
- Develops and enhances Power BI datasets, semantic models, reports, dashboards, measures, filters, and user experiences; applies established reporting and analytic standards to promote consistent interpretation of investment data.
- Partners with business users and Technology teams to define requirements, evaluate source-system and downstream impacts, document technical designs, estimate work, and sequence delivery through an agile work process.
- Performs complex data profiling, reconciliation, and validation across investment data sources; establishes data-quality checks, exception handling, monitoring, and operational procedures to identify and resolve issues before they affect consumers.
- Supports end-to-end testing, including test scenario development, data validation, regression testing, User Acceptance Testing, defect triage, release readiness, and post-release verification.
- Collaborates with data governance, data management, reporting, infrastructure, vendor, and investment-business partners to ensure data access, security, controls, and audit expectations are met.
- Evaluates and applies emerging artificial intelligence capabilities responsibly, including AI-assisted documentation, natural-language interaction with data, data-quality monitoring, summarization, and other use cases that improve productivity or access to governed information.
- Communicates technical concepts clearly to audiences with varying levels of technical expertise; facilitates working sessions, presents recommendations, provides status and risk updates, and builds consensus around data and reporting solutions.
- Participates in production support and operational activities, including monitoring scheduled processes, reviewing exceptions, reloading or correcting data when appropriate, coordinating incident resolution, and communicating impacts to stakeholders.
Now "Job Description Key Responsibilities:" list:
- Identifies, executes, and communicates data strategy opportunities, defining long-term goals and key performance indicators to further a data-driven culture in support of business priorities.
- Consults and provides direction on acquisition, curation, and consumption of data for analytical and operational uses, producing data source documentation and assisting with development and maintenance of reference data and mastering rules to ensure a single version of the truth across all data consumers.
- Collaborates on mapping the end-to-end flow of data and the business processes and/or technical interfaces which would be created or impacted and recommends solutions/adaptations.
- Develops collaborative relationships with business, Technology, and vendor partners, communicating data impacts and promoting transparency around data issue identification and resolution.
- Prompts data, reporting and analytic requirements from business requestors to generate solutions.
- Participates in planning and execution of UAT, triage issues and works with development team on remediation approach to ensure data integrity.
- Performs data management activities, including classifying information into logical categories, generating data lineage, developing data quality and transformation rules, conducting complex data profiling, implementing data monitoring techniques using standardized tools, reviewing daily exceptions, reloading data, and applying data overrides as necessary.
- Uses moderate to complex visualization techniques and skills to present data in support of business needs.
- Enforces data governance structure, standards, and procedures to ensure data is well-defined, consistent, accurate, accessible, and secure.
- Governs all data access requests and has final right of refusal for accesses.
- Demonstrates knowledge and understanding of investment asset classes, and those data elements most critical to support business processes.
- Integrates emerging data and analytic trends, competitive research, and industry best practices into Nationwide.
- May Perform Other Responsibilities As Assigned.
- Reporting Relationships: Reports to AVP or Data Leader
- Typical Skills And Experiences Education: Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred. Graduate studies in business, statistics, math, computer science or a related field are a plus. License/Certification/Designation: Certifications are not required but encouraged. Experience: 6-10 years of relevant experience with data management organization/standards or practices. Experience engaging business leaders, data architects and external consultants to identify and fill gaps in data and analytics environmen
Note: The last part seems cut off. But we need to preserve as is.
We see some overlap: e.g., "Performs complex data profiling..." appears in both. Also "Participates in planning and execution of UAT..." similar. We need to deduplicate.
We'll combine unique items.
Let's list all unique responsibilities:
From first list (I'll label them A1-A12). From second list (B1-B...).
I'll compile set.
First list items:
1. Designs, develops, and maintains data models, curated datasets, semantic models, and data products that support investment reporting, analytics, operational processes, and self-service business intelligence.
2. Builds, supports, and troubleshoots data pipelines, dataflows, notebooks, jobs, scheduled processes, and related integrations; investigates failures, identifies root causes, and coordinates timely remediation.
3. Uses data modeling principles to define relationships, business rules, transformations, keys, hierarchies, measures, and other structures needed to create consistent and reusable data products.
4. Creates and maintains Business Objects universes, reports, scheduled distributions, and related reporting components, while supporting the transition of legacy reporting capabilities to modern, governed solutions where appropriate.
5. Develops and enhances Power BI datasets, semantic models, reports, dashboards, measures, filters, and user experiences; applies established reporting and analytic standards to promote consistent interpretation of investment data.
6. Partners with business users and Technology teams to define requirements, evaluate source-system and downstream impacts, document technical designs, estimate work, and sequence delivery through an agile work process.
7. Performs complex data profiling, reconciliation, and validation across investment data sources; establishes data-quality checks, exception handling, monitoring, and operational procedures to identify and resolve issues before they affect consumers.
8. Supports end-to-end testing, including test scenario development, data validation, regression testing, User Acceptance Testing, defect triage, release readiness, and post-release verification.
9. Collaborates with data governance, data management, reporting, infrastructure, vendor, and investment-business partners to ensure data access, security, controls, and audit expectations are met.
10. Evaluates and applies emerging artificial intelligence capabilities responsibly, including AI-assisted documentation, natural-language interaction with data, data-quality monitoring, summarization, and other use cases that improve productivity or access to governed information.
11. Communicates technical concepts clearly to audiences with varying levels of technical expertise; facilitates working sessions, presents recommendations, provides status and risk updates, and builds consensus around data and reporting solutions.
12. Participates in production support and operational activities, including monitoring scheduled processes, reviewing exceptions, reloading or correcting data when appropriate, coordinating incident resolution, and communicating impacts to stakeholders.
Second list items:
13. Identifies, executes, and communicates data strategy opportunities, defining long-term goals and key performance indicators to further a data-driven culture in support of business priorities.
14. Consults and provides direction on acquisition, curation, and consumption of data for analytical and operational uses, producing data source documentation and assisting with development and maintenance of reference data and mastering rules to ensure a single version of the truth across all data consumers.
15. Collaborates on mapping the end-to-end flow of data and the business processes and/or technical interfaces which would be created or impacted and recommends solutions/adaptations.
16. Develops collaborative relationships with business, Technology, and vendor partners, communicating data impacts and promoting transparency around data issue identification and resolution.
17. Prompts data, reporting and analytic requirements from business requestors to generate solutions.
18. Participates in planning and execution of UAT, triage issues and works with development team on remediation approach to ensure data integrity.
19. Performs data management activities, including classifying information into logical categories, generating data lineage, developing data quality and transformation rules, conducting complex data profiling, implementing data monitoring techniques using standardized tools, reviewing daily exceptions, reloading data, and applying data overrides as necessary.
20. Uses moderate to complex visualization
for prose. We need to preserve all substantive information; do not invent or summarize away detail. Must not omit details. We need to decide which sections to include: About the role (intro), Responsibilities, Requirements (maybe combine Technical Requirements and Preferred Qualifications?), Qualifications (maybe separate?), Skills (maybe technical skills?), Schedule. But we must not create thin sections. Prefer few substantive sections. We could have sections: About the role (intro paragraph), Responsibilities (list), Requirements (list), Schedule (p). Possibly also Qualifications (but could merge with Requirements). The posting has "Technical Requirements And Experience" and "Preferred Qualifications". Also "Success in This Role" and "Role Summary". Could combine into About the role. We need to ensure we don't leave empty sections. Let's extract substantive content: Intro: "As a team member in Finance at Nationwide, a Fortune 100 company with nearly $70 billion in annual sales, the opportunities are endless! Let Nationwide help create your career journey! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care. The Investment Data Management professional supporting Data Insights will translate investment-business needs into reliable, governed data products and business intelligence solutions. This position combines business partnership with hands-on technical delivery across cloud data platforms, data models, reporting tools, and emerging artificial intelligence capabilities." That's about the role. Responsibilities: There's a big list under "Key Responsibilities Include" and later "Job Description Key Responsibilities:" which seems to repeat or expand. We need to preserve all, not duplicate? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." If there are duplicates, we might need to include them? It says remove duplicated lines. So we should deduplicate. We need to combine responsibilities from both sections, removing duplicates. Let's list responsibilities from first "Key Responsibilities Include": - Designs, develops, and maintains data models, curated datasets, semantic models, and data products that support investment reporting, analytics, operational processes, and self-service business intelligence. - Builds, supports, and troubleshoots data pipelines, dataflows, notebooks, jobs, scheduled processes, and related integrations; investigates failures, identifies root causes, and coordinates timely remediation. - Uses data modeling principles to define relationships, business rules, transformations, keys, hierarchies, measures, and other structures needed to create consistent and reusable data products. - Creates and maintains Business Objects universes, reports, scheduled distributions, and related reporting components, while supporting the transition of legacy reporting capabilities to modern, governed solutions where appropriate. - Develops and enhances Power BI datasets, semantic models, reports, dashboards, measures, filters, and user experiences; applies established reporting and analytic standards to promote consistent interpretation of investment data. - Partners with business users and Technology teams to define requirements, evaluate source-system and downstream impacts, document technical designs, estimate work, and sequence delivery through an agile work process. - Performs complex data profiling, reconciliation, and validation across investment data sources; establishes data-quality checks, exception handling, monitoring, and operational procedures to identify and resolve issues before they affect consumers. - Supports end-to-end testing, including test scenario development, data validation, regression testing, User Acceptance Testing, defect triage, release readiness, and post-release verification. - Collaborates with data governance, data management, reporting, infrastructure, vendor, and investment-business partners to ensure data access, security, controls, and audit expectations are met. - Evaluates and applies emerging artificial intelligence capabilities responsibly, including AI-assisted documentation, natural-language interaction with data, data-quality monitoring, summarization, and other use cases that improve productivity or access to governed information. - Communicates technical concepts clearly to audiences with varying levels of technical expertise; facilitates working sessions, presents recommendations, provides status and risk updates, and builds consensus around data and reporting solutions. - Participates in production support and operational activities, including monitoring scheduled processes, reviewing exceptions, reloading or correcting data when appropriate, coordinating incident resolution, and communicating impacts to stakeholders. Now "Job Description Key Responsibilities:" list: - Identifies, executes, and communicates data strategy opportunities, defining long-term goals and key performance indicators to further a data-driven culture in support of business priorities. - Consults and provides direction on acquisition, curation, and consumption of data for analytical and operational uses, producing data source documentation and assisting with development and maintenance of reference data and mastering rules to ensure a single version of the truth across all data consumers. - Collaborates on mapping the end-to-end flow of data and the business processes and/or technical interfaces which would be created or impacted and recommends solutions/adaptations. - Develops collaborative relationships with business, Technology, and vendor partners, communicating data impacts and promoting transparency around data issue identification and resolution. - Prompts data, reporting and analytic requirements from business requestors to generate solutions. - Participates in planning and execution of UAT, triage issues and works with development team on remediation approach to ensure data integrity. - Performs data management activities, including classifying information into logical categories, generating data lineage, developing data quality and transformation rules, conducting complex data profiling, implementing data monitoring techniques using standardized tools, reviewing daily exceptions, reloading data, and applying data overrides as necessary. - Uses moderate to complex visualization techniques and skills to present data in support of business needs. - Enforces data governance structure, standards, and procedures to ensure data is well-defined, consistent, accurate, accessible, and secure. - Governs all data access requests and has final right of refusal for accesses. - Demonstrates knowledge and understanding of investment asset classes, and those data elements most critical to support business processes. - Integrates emerging data and analytic trends, competitive research, and industry best practices into Nationwide. - May Perform Other Responsibilities As Assigned. - Reporting Relationships: Reports to AVP or Data Leader - Typical Skills And Experiences Education: Undergraduate studies in computer science, management information systems, business, statistics, math, a related field or comparable experience and education strongly preferred. Graduate studies in business, statistics, math, computer science or a related field are a plus. License/Certification/Designation: Certifications are not required but encouraged. Experience: 6-10 years of relevant experience with data management organization/standards or practices. Experience engaging business leaders, data architects and external consultants to identify and fill gaps in data and analytics environmen Note: The last part seems cut off. But we need to preserve as is. We see some overlap: e.g., "Performs complex data profiling..." appears in both. Also "Participates in planning and execution of UAT..." similar. We need to deduplicate. We'll combine unique items. Let's list all unique responsibilities: From first list (I'll label them A1-A12). From second list (B1-B...). I'll compile set. First list items: 1. Designs, develops, and maintains data models, curated datasets, semantic models, and data products that support investment reporting, analytics, operational processes, and self-service business intelligence. 2. Builds, supports, and troubleshoots data pipelines, dataflows, notebooks, jobs, scheduled processes, and related integrations; investigates failures, identifies root causes, and coordinates timely remediation. 3. Uses data modeling principles to define relationships, business rules, transformations, keys, hierarchies, measures, and other structures needed to create consistent and reusable data products. 4. Creates and maintains Business Objects universes, reports, scheduled distributions, and related reporting components, while supporting the transition of legacy reporting capabilities to modern, governed solutions where appropriate. 5. Develops and enhances Power BI datasets, semantic models, reports, dashboards, measures, filters, and user experiences; applies established reporting and analytic standards to promote consistent interpretation of investment data. 6. Partners with business users and Technology teams to define requirements, evaluate source-system and downstream impacts, document technical designs, estimate work, and sequence delivery through an agile work process. 7. Performs complex data profiling, reconciliation, and validation across investment data sources; establishes data-quality checks, exception handling, monitoring, and operational procedures to identify and resolve issues before they affect consumers. 8. Supports end-to-end testing, including test scenario development, data validation, regression testing, User Acceptance Testing, defect triage, release readiness, and post-release verification. 9. Collaborates with data governance, data management, reporting, infrastructure, vendor, and investment-business partners to ensure data access, security, controls, and audit expectations are met. 10. Evaluates and applies emerging artificial intelligence capabilities responsibly, including AI-assisted documentation, natural-language interaction with data, data-quality monitoring, summarization, and other use cases that improve productivity or access to governed information. 11. Communicates technical concepts clearly to audiences with varying levels of technical expertise; facilitates working sessions, presents recommendations, provides status and risk updates, and builds consensus around data and reporting solutions. 12. Participates in production support and operational activities, including monitoring scheduled processes, reviewing exceptions, reloading or correcting data when appropriate, coordinating incident resolution, and communicating impacts to stakeholders. Second list items: 13. Identifies, executes, and communicates data strategy opportunities, defining long-term goals and key performance indicators to further a data-driven culture in support of business priorities. 14. Consults and provides direction on acquisition, curation, and consumption of data for analytical and operational uses, producing data source documentation and assisting with development and maintenance of reference data and mastering rules to ensure a single version of the truth across all data consumers. 15. Collaborates on mapping the end-to-end flow of data and the business processes and/or technical interfaces which would be created or impacted and recommends solutions/adaptations. 16. Develops collaborative relationships with business, Technology, and vendor partners, communicating data impacts and promoting transparency around data issue identification and resolution. 17. Prompts data, reporting and analytic requirements from business requestors to generate solutions. 18. Participates in planning and execution of UAT, triage issues and works with development team on remediation approach to ensure data integrity. 19. Performs data management activities, including classifying information into logical categories, generating data lineage, developing data quality and transformation rules, conducting complex data profiling, implementing data monitoring techniques using standardized tools, reviewing daily exceptions, reloading data, and applying data overrides as necessary. 20. Uses moderate to complex visualization