bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesEkcf Fa Us6 Oraclecloud Com Cx 1Data Analyst

Data Analyst

Ekcf Fa Us6 Oraclecloud Com Cx 1 · Houston, TX, United States; Houston TX Airport (Corp), Houston, TX, US · Active · Oracle Recruiting Cloud / Fusion HCM

Job facts

FieldValue
CompanyEkcf Fa Us6 Oraclecloud Com Cx 1
TitleData Analyst
Normalized title-
Department / teamInformation Technology
LocationHouston, TX, United States
Work model-
Employment typeFull Time
Salary-
Statusactive
ATS providerOracle Recruiting Cloud / Fusion HCM
Posted / first seen2026-06-03 / 2026-06-04
Changed / last seen2026-06-04 / 2026-06-04

Related slices

PageWhat it containsOpen
Company jobsActive postings from Ekcf Fa Us6 Oraclecloud Com Cx 1.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Oracle Recruiting Cloud / Fusion HCM.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Houston.Open
Department jobsActive postings in Information Technology.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyEkcf Fa Us6 Oraclecloud Com Cx 1
Sourcec0937d7f-2670-468c-a687-5bab8a66cd3f
ATS providerOracle Recruiting Cloud / Fusion HCM

Description

Description Powell Industries is in the middle of a meaningful shift in how we use data to run the business. Over the years, our teams have developed genuine ingenuity to make data work for them: curating Excel exports, building secondary processes to transform and distribute information, and creating workarounds that keep operations running even when the underlying systems were not designed with that in mind. What we are doing now is taking that same ingenuity and re-baselining it on a modern platform — one where those workarounds can be de-siloed, prototyped freshly, and properly collaborated upon, enabled by a central team focused on maintaining a meaningful balance between delivery and enabling democratization of delivery. The institutional knowledge embedded in those Excel files and secondary processes does not disappear; it becomes the starting point for something governed, shared, and built to last. The time to ramp up on this new approach has come, and with it, the steps to move on from the legacy tools that have carried us this far. The Data Analyst sits at the center of that transition — helping translate business questions into trusted data products, accelerating the shift from report-pulling to genuine self-serve analytics, and compressing the time between a question and a confident answer. Critically, that means making insights actionable within the data experience itself, not as a downstream step. And where possible, closing the loop upstream too: bringing data entry and collection into the same coherent surface. What you will work on Making data accessible and actionable Own and evolve the semantic data models and governed views that serve as the trusted foundation for workbooks, apps, and workflows built across the business — ensuring that what gets built on top is built on something solid, consistent, and shared. Enable builders, collectors, and reviewers across the business to work independently in Sigma — not by building for them, but by ensuring the underlying data model is well-defined, well-documented, and expressive enough that they can construct what they need without hitting a wall. Where AI tools can shorten that path — through prompt-driven query generation, notebook-based analysis, or faster pattern recognition — use them; the goal is a faster answer, not a showcase of the tooling. Curate and maintain common definitions, reusable metrics, and shared business logic so that teams across the organization are working from the same numbers — regardless of which surface, workbook, or workflow they are using to access them. Where the business has questions that structured data alone cannot answer — documents, emails, field notes, unstructured inputs of any kind — our underlying data platform unlocks the ability to bring that context into the analytical surface, alongside direct access to AI models. This is not a standing deliverable; it moves at the pace of genuine demand. Distinguishing analytics from operational reporting Help the organization develop sharper instincts about the difference between operational metrics (what happened, is it in spec, does it need action today) and strategic analytics (why is it happening, what should we do about it). This distinction shapes what gets built, how fast it needs to update, and who needs to see it. Work iteratively with business teams to understand what they are actually asking, not just what they think they can request from a data system — and translate that understanding back into better models, cleaner definitions, and sharper questions. Automating the repeatable Identify manual, recurring data workflows — the Monday-morning Excel refresh, the end-of-month report, the ad hoc pivot rebuilt from scratch every quarter — and replace them with automated, auditable pipelines that run without anyone asking. Identify patterns in the most frequently asked business questions and build reusable, parameterized notebooks and templates that make expert-quality analysis available without requiring an expert every time. Write clean SQL and Python to support automation, data validation, and lightweight transformation work on top of our cloud data platform. What we are looking for You will need Solid SQL — comfortable querying, filtering, joining, and aggregating in a cloud data warehouse environment. Familiarity with how modern data platforms are structured matters more than experience with any specific one. Working Python — enough to write scripts, automate data tasks, and work confidently in notebook environments (Jupyter, Marimo, or similar). An instinct for clarity — you ask what a number means before you put it in a chart, and you notice when a metric definition creates more confusion than it resolves. Comfort with ambiguity — business questions rarely arrive fully formed, and you are good at turning a vague ask into a concrete, answerable question. Curiosity about AI tooling — you have used LLM-based tools to accelerate your own work and are interested in how they can make data accessible to people who do not think of themselves as data people. Nice to have Experience with Sigma Computing or a comparable modern BI platform (Tableau, Looker, Power BI). Exposure to dbt or semantic modelling concepts. Any experience in a manufacturing, industrial, or operations-heavy environment — you will understand the data faster. Familiarity with pipeline orchestration or workflow automation tools. Company In our 75+ year history, Powell has always known that our employees are at the heart of our success. Without question, we have the most talented people in all parts of our organization. As a manufacturer, we recruit and hire experienced and knowledgeable applicants to ensure our product is engineered, fabricated, and assembled to customer specifications! Powell’s culture has and will always be founded in our "can do" attitude. If we can imagine it, we can do it. Become a part of our story and let us help you write yours. Hard work pays off in all our teams, with opportunity for advancement and promotion without sacrificing work-life balance. Successful candidates must have a legal authorization to work in the United States on a full-time basis, with only those candidates selected for interview contacted. Powell offers comprehensive health insurance for you and your family, 401k savings, annual bonus potential, generous paid time off, professional development opportunities, company-sponsored wellness programs, and a collaborative work environment. EOE Protected Veterans/Disability If you need an accommodation in the hiring process, you may contact 713.378.2685. Application status inquiries will not be accepted in this manner.

Full job record

Job ID198a5082ea21ec80eb0a2a300046cd46c75c9d15
Org ID44323a67-6864-497d-a978-7e5fe6805dbe
Source IDc0937d7f-2670-468c-a687-5bab8a66cd3f
Board IDc0937d7f-2670-468c-a687-5bab8a66cd3f
Provideroracle_hcm
Provider Job Key7187
TitleData Analyst
Normalized Title
Statusactive
Activeyes
Location TextHouston, TX, United States; Houston TX Airport (Corp), Houston, TX, US
DepartmentInformation Technology
Team
Employment Typefull_time
Workplace Type
Remote Policy
CountryUnited States
RegionTX
CityHouston
Salary RawDescription Powell Industries is in the middle of a meaningful shift in how we use data to run the business. Over the years, our teams have developed genuine ingenuity to make data work for them: curating Excel exports, building secondary processes to transform and distribute information, and creating workarounds that keep operations running even when the underlying systems were not designed with that in mind. What we are doing now is taking that same ingenuity and re-baselining it on a modern platform — one where those workarounds can be de-siloed, prototyped freshly, and properly collaborated upon, enabled by a central team focused on maintaining a meaningful balance between delivery and enabling democratization of delivery. The institutional knowledge embedded in those Excel files and secondary processes does not disappear; it becomes the starting point for something governed, shared, and built to last. The time to ramp up on this new approach has come, and with it, the steps to move on from the legacy tools that have carried us this far. The Data Analyst sits at the center of that transition — helping translate business questions into trusted data products, accelerating the shift from report-pulling to genuine self-serve analytics, and compressing the time between a question and a confident answer. Critically, that means making insights actionable within the data experience itself, not as a downstream step. And where possible, closing the loop upstream too: bringing data entry and collection into the same coherent surface. What you will work on Making data accessible and actionable Own and evolve the semantic data models and governed views that serve as the trusted foundation for workbooks, apps, and workflows built across the business — ensuring that what gets built on top is built on something solid, consistent, and shared. Enable builders, collectors, and reviewers across the business to work independently in Sigma — not by building for them, but by ensuring the underlying data model is well-defined, well-documented, and expressive enough that they can construct what they need without hitting a wall. Where AI tools can shorten that path — through prompt-driven query generation, notebook-based analysis, or faster pattern recognition — use them; the goal is a faster answer, not a showcase of the tooling. Curate and maintain common definitions, reusable metrics, and shared business logic so that teams across the organization are working from the same numbers — regardless of which surface, workbook, or workflow they are using to access them. Where the business has questions that structured data alone cannot answer — documents, emails, field notes, unstructured inputs of any kind — our underlying data platform unlocks the ability to bring that context into the analytical surface, alongside direct access to AI models. This is not a standing deliverable; it moves at the pace of genuine demand. Distinguishing analytics from operational reporting Help the organization develop sharper instincts about the difference between operational metrics (what happened, is it in spec, does it need action today) and strategic analytics (why is it happening, what should we do about it). This distinction shapes what gets built, how fast it needs to update, and who needs to see it. Work iteratively with business teams to understand what they are actually asking, not just what they think they can request from a data system — and translate that understanding back into better models, cleaner definitions, and sharper questions. Automating the repeatable Identify manual, recurring data workflows — the Monday-morning Excel refresh, the end-of-month report, the ad hoc pivot rebuilt from scratch every quarter — and replace them with automated, auditable pipelines that run without anyone asking. Identify patterns in the most frequently asked business questions and build reusable, parameterized notebooks and templates that make expert-quality analysis available without requiring an expert every time. Write clean SQL and Python to support automation, data validation, and lightweight transformation work on top of our cloud data platform. What we are looking for You will need Solid SQL — comfortable querying, filtering, joining, and aggregating in a cloud data warehouse environment. Familiarity with how modern data platforms are structured matters more than experience with any specific one. Working Python — enough to write scripts, automate data tasks, and work confidently in notebook environments (Jupyter, Marimo, or similar). An instinct for clarity — you ask what a number means before you put it in a chart, and you notice when a metric definition creates more confusion than it resolves. Comfort with ambiguity — business questions rarely arrive fully formed, and you are good at turning a vague ask into a concrete, answerable question. Curiosity about AI tooling — you have used LLM-based tools to accelerate your own work and are interested in how they can make data accessible to people who do not think of themselves as data people. Nice to have Experience with Sigma Computing or a comparable modern BI platform (Tableau, Looker, Power BI). Exposure to dbt or semantic modelling concepts. Any experience in a manufacturing, industrial, or operations-heavy environment — you will understand the data faster. Familiarity with pipeline orchestration or workflow automation tools. Company In our 75+ year history, Powell has always known that our employees are at the heart of our success. Without question, we have the most talented people in all parts of our organization. As a manufacturer, we recruit and hire experienced and knowledgeable applicants to ensure our product is engineered, fabricated, and assembled to customer specifications! Powell’s culture has and will always be founded in our "can do" attitude. If we can imagine it, we can do it. Become a part of our story and let us help you write yours. Hard work pays off in all our teams, with opportunity for advancement and promotion without sacrificing work-life balance. Successful candidates must have a legal authorization to work in the United States on a full-time basis, with only those candidates selected for interview contacted. Powell offers comprehensive health insurance for you and your family, 401k savings, annual bonus potential, generous paid time off, professional development opportunities, company-sponsored wellness programs, and a collaborative work environment. EOE Protected Veterans/Disability If you need an accommodation in the hiring process, you may contact 713.378.2685. Application status inquiries will not be accepted in this manner.
Salary Min
Salary Max
Salary Currency
Salary Periodmonth
Source URLhttps://ekcf.fa.us6.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_1/job/7187
Apply URLhttps://ekcf.fa.us6.oraclecloud.com/hcmUI/CandidateExperience/en/sites/cx_1/job/7187
First Seen At2026-06-04 10:52:13Z
Last Seen At2026-06-04 10:52:13Z
Last Checked At2026-06-04 10:52:13Z
Last Changed At2026-06-04 10:52:13Z
Inactive At
Source Posted At2026-06-03 18:35:47Z
Source Updated At
Raw Payload Uris3://bluework-jobs-prod-raw-590183727216/raw/provider=oracle_hcm/board=ekcf.fa.us6.oraclecloud.com|cx_1/date=2026-06-04/2026-06-04T10-52-03-353Z-53b252d91052330c42b1388d8ce8446337824717ab6a5e6e7bf95075833082f7.json
Event Fields
{
  "content_hash": "a1558f062176a854e78731d879149d411e1266b816d286ab13d111adce464191",
  "source_hash": "31942d9363292167bf21e969dae50291b03353026a526702e223674579abcf8f",
  "last_changed_at": "2026-06-04T10:52:13.668Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "Houston, TX, United States",
    "city": "Houston",
    "region": "TX",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": null,
  "salary_min": null,
  "inferred_at": "2026-06-04T10:52:13.467Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "Houston, TX, United States",
      "city": "Houston",
      "region": "TX",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": "month",
  "workplace_type": null,
  "salary_currency": null
}
Extensions
{}
Native Structured
{
  "detail": {
    "Id": "7187",
    "Title": "Data Analyst",
    "media": [],
    "skills": [],
    "JobType": null,
    "Category": "Information Technology",
    "JobGrade": null,
    "JobLevel": null,
    "JobShift": "1st Shift",
    "WorkDays": null,
    "WorkHours": null,
    "WorkYears": null,
    "Department": null,
    "HotJobFlag": false,
    "StudyLevel": null,
    "WorkMonths": null,
    "WorkerType": null,
    "GeographyId": 300000001930504,
    "JobFamilyId": 300000006157329,
    "JobFunction": null,
    "JobSchedule": "Full time",
    "BusinessUnit": null,
    "ContractType": null,
    "Organization": null,
    "TrendingFlag": true,
    "workLocation": [
      {
        "Country": "US",
        "Region1": "Harris",
        "Region2": "TX",
        "Region3": null,
        "Building": null,
        "Latitude": "29.65944",
        "Longitude": "-95.28168",
        "LocationId": 300000006175560,
        "PostalCode": "77061",
        "TownOrCity": "Houston",
        "AddressLine1": "7232 Airport Blvd",
        "AddressLine2": null,
        "AddressLine3": null,
        "AddressLine4": null,
        "LocationName": "Houston TX Airport (Corp)"
      }
    ],
    "ContentLocale": "en",
    "HiringManager": null,
    "LegalEmployer": null,
    "RequisitionId": 300000982915438,
    "WorkplaceType": "",
    "BusinessUnitId": 300000001791607,
    "OrganizationId": 1,
    "GeographyNodeId": 100003943373872,
    "JobFunctionCode": null,
    "LegalEmployerId": 300000001793021,
    "PrimaryLocation": "Houston, TX, United States",
    "RequisitionType": "Salaried",
    "NumberOfOpenings": null,
    "WorkplaceTypeCode": null,
    "BeFirstToApplyFlag": false,
    "otherWorkLocations": [],
    "secondaryLocations": [],
    "ExternalContactName": null,
    "ShortDescriptionStr": "",
    "ExternalContactEmail": null,
    "ExternalPostedEndDate": null,
    "OtherRequisitionTitle": null,
    "requisitionFlexFields": [],
    "ApplyWhenNotPostedFlag": null,
    "DomesticTravelRequired": null,
    "ExternalDescriptionStr": "<p style=\"margin: 3pt 0in;\">Powell Industries is in the middle of a meaningful shift in how we use data to run the business. Over the years, our teams have developed genuine ingenuity to make data work for them: curating Excel exports, building secondary processes to transform and distribute information, and creating workarounds that keep operations running even when the underlying systems were not designed with that in mind.</p><p style=\"margin: 3pt 0in;\">What we are doing now is taking that same ingenuity and re-baselining it on a modern platform — one where those workarounds can be de-siloed, prototyped freshly, and properly collaborated upon, enabled by a central team focused on maintaining a meaningful balance between delivery and enabling democratization of delivery. The institutional knowledge embedded in those Excel files and secondary processes does not disappear; it becomes the starting point for something governed, shared, and built to last. The time to ramp up on this new approach has come, and with it, the steps to move on from the legacy tools that have carried us this far.</p><p style=\"margin: 3pt 0in;\">The Data Analyst sits at the center of that transition — helping translate business questions into trusted data products, accelerating the shift from report-pulling to genuine self-serve analytics, and compressing the time between a question and a confident answer. Critically, that means making insights actionable within the data experience itself, not as a downstream step. And where possible, closing the loop upstream too: bringing data entry and collection into the same coherent surface.</p><div style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; padding: 0in 0in 4pt;\"><p class=\"heading10\" style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; padding: 0in;\"><strong><u>What you will work on</u></strong></p></div><p class=\"heading20\"><strong>Making data accessible and actionable</strong></p><ul style=\"padding-left: 48px;\"><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Own and evolve the semantic data models and governed views that serve as the trusted foundation for workbooks, apps, and workflows built across the business — ensuring that what gets built on top is built on something solid, consistent, and shared.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Enable builders, collectors, and reviewers across the business to work independently in Sigma — not by building for them, but by ensuring the underlying data model is well-defined, well-documented, and expressive enough that they can construct what they need without hitting a wall. Where AI tools can shorten that path — through prompt-driven query generation, notebook-based analysis, or faster pattern recognition — use them; the goal is a faster answer, not a showcase of the tooling.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Curate and maintain common definitions, reusable metrics, and shared business logic so that teams across the organization are working from the same numbers — regardless of which surface, workbook, or workflow they are using to access them.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Where the business has questions that structured data alone cannot answer — documents, emails, field notes, unstructured inputs of any kind — our underlying data platform unlocks the ability to bring that context into the analytical surface, alongside direct access to AI models. This is not a standing deliverable; it moves at the pace of genuine demand.</p></li></ul><p class=\"heading20\"><strong>Distinguishing analytics from operational reporting</strong></p><ul style=\"padding-left: 48px;\"><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Help the organization develop sharper instincts about the difference between operational metrics (what happened, is it in spec, does it need action today) and strategic analytics (why is it happening, what should we do about it). This distinction shapes what gets built, how fast it needs to update, and who needs to see it.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Work iteratively with business teams to understand what they are actually asking, not just what they think they can request from a data system — and translate that understanding back into better models, cleaner definitions, and sharper questions.</p></li></ul><p class=\"heading20\"><strong>Automating the repeatable</strong></p><ul style=\"padding-left: 48px;\"><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Identify manual, recurring data workflows — the Monday-morning Excel refresh, the end-of-month report, the ad hoc pivot rebuilt from scratch every quarter — and replace them with automated, auditable pipelines that run without anyone asking.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Identify patterns in the most frequently asked business questions and build reusable, parameterized notebooks and templates that make expert-quality analysis available without requiring an expert every time.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Write clean SQL and Python to support automation, data validation, and lightweight transformation work on top of our cloud data platform.</p></li></ul><div style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; padding: 0in 0in 4pt;\"><p class=\"heading10\" style=\"border-width: medium; border-style: none; border-color: currentcolor; border-image: initial; padding: 0in;\"><strong><u>What we are looking for</u></strong></p></div><p class=\"heading20\"><strong>You will need</strong></p><ul style=\"padding-left: 48px;\"><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Solid SQL — comfortable querying, filtering, joining, and aggregating in a cloud data warehouse environment. Familiarity with how modern data platforms are structured matters more than experience with any specific one.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Working Python — enough to write scripts, automate data tasks, and work confidently in notebook environments (Jupyter, Marimo, or similar).</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">An instinct for clarity — you ask what a number means before you put it in a chart, and you notice when a metric definition creates more confusion than it resolves.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Comfort with ambiguity — business questions rarely arrive fully formed, and you are good at turning a vague ask into a concrete, answerable question.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Curiosity about AI tooling — you have used LLM-based tools to accelerate your own work and are interested in how they can make data accessible to people who do not think of themselves as data people.</p></li></ul><p class=\"heading20\"><strong>Nice to have</strong></p><ul style=\"padding-left: 48px;\"><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Experience with Sigma Computing or a comparable modern BI platform (Tableau, Looker, Power BI).</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Exposure to dbt or semantic modelling concepts.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Any experience in a manufacturing, industrial, or operations-heavy environment — you will understand the data faster.</p></li><li><p style=\"margin-bottom: 2pt; margin-right: 0in; margin-top: 2pt;\">Familiarity with pipeline orchestration or workflow automation tools.</p></li></ul>",
    "ObjectVerNumberProfile": "1",
    "PrimaryLocationCountry": "US",
    "CorporateDescriptionStr": "<div>\n In our 75+ year history, Powell has always known that our employees are at the heart of our success. Without question, we have the most talented people in all parts of our organization. As a manufacturer, we recruit and hire experienced and knowledgeable applicants to ensure our product is engineered, fabricated, and assembled to customer specifications!\n</div>\n<div>\n Powell’s culture has and will always be founded in our \"can do\" attitude. If we can imagine it, we can do it. Become a part of our story and let us help you write yours. Hard work pays off in all our teams, with opportunity for advancement and promotion without sacrificing work-life balance. Successful candidates must have a legal authorization to work in the United States on a full-time basis, with only those candidates selected for interview contacted.\n</div>\n<div>\n Powell offers comprehensive health insurance for you and your family, 401k savings, annual bonus potential, generous paid time off, professional development opportunities, company-sponsored wellness programs, and a collaborative work environment.\n</div>\n<div>\n EOE Protected Veterans/Disability\n</div>\n<div>\n If you need an accommodation in the hiring process, you may contact 713.378.2685. Application status inquiries will not be accepted in this manner.\n</div>",
    "ExternalPostedStartDate": "2026-06-03T18:35:47+00:00",
    "ExternalQualificationsStr": "",
    "InternalQualificationsStr": "",
    "OrganizationDescriptionStr": "",
    "primaryLocationCoordinates": [
      {
        "Latitude": "30.04692",
        "Longitude": "-95.24648",
        "CountryCode": "US",
        "GeographyId": 300000001930504,
        "GeographyNodeId": 100003943373872
      }
    ],
    "ExternalResponsibilitiesStr": "",
    "InternalResponsibilitiesStr": "",
    "InternationalTravelRequired": null
  },
  "list_job": {
    "Id": "7187",
    "Title": "Data Analyst",
    "JobType": null,
    "Distance": 1780444800000,
    "JobShift": null,
    "Language": "US",
    "WorkDays": null,
    "JobFamily": null,
    "Relevancy": 9,
    "WorkHours": null,
    "Department": null,
    "HotJobFlag": false,
    "PostedDate": "2026-06-03",
    "StudyLevel": null,
    "WorkerType": null,
    "GeographyId": 300000001930504,
    "JobFunction": null,
    "JobSchedule": null,
    "BusinessUnit": null,
    "ContractType": null,
    "ManagerLevel": null,
    "Organization": null,
    "TrendingFlag": true,
    "workLocation": [
      {
        "Country": "US",
        "Region1": "Harris",
        "Region2": "TX",
        "Region3": null,
        "Building": null,
        "Latitude": 29.65944,
        "Longitude": -95.28168,
        "LocationId": 300000006175560,
        "PostalCode": "77061",
        "TownOrCity": "Houston",
        "AddressLine1": "7232 Airport Blvd",
        "AddressLine2": null,
        "AddressLine3": null,
        "AddressLine4": null,
        "LocationName": "Houston TX Airport (Corp)"
      }
    ],
    "LegalEmployer": null,
    "MediaThumbURL": null,
    "WorkplaceType": "",
    "BusinessUnitId": 300000001791607,
    "OrganizationId": 1,
    "PostingEndDate": null,
    "LegalEmployerId": 300000001793021,
    "PrimaryLocation": "Houston, TX, United States",
    "WorkDurationYears": null,
    "WorkplaceTypeCode": null,
    "BeFirstToApplyFlag": false,
    "WorkDurationMonths": null,
    "otherWorkLocations": [],
    "secondaryLocations": [],
    "ShortDescriptionStr": "",
    "requisitionFlexFields": [],
    "DomesticTravelRequired": null,
    "PrimaryLocationCountry": "US",
    "ExternalQualificationsStr": null,
    "ExternalResponsibilitiesStr": null,
    "InternationalTravelRequired": null
  },
  "detail_meta": {
    "url": "https://ekcf.fa.us6.oraclecloud.com/hcmRestApi/resources/latest/recruitingCEJobRequisitionDetails?expand=all&onlyData=true&finder=ById;Id=%227187%22,siteNumber=cx_1",
    "http_status": 200,
    "content_type": "application/json",
    "response_bytes": 12401
  },
  "detail_errors": []
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/198a5082ea21ec80eb0a2a300046cd46c75c9d15?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/44323a67-6864-497d-a978-7e5fe6805dbeJSON
GET https://api.bluedoor.sh/job-postings/v1/sources/c0937d7f-2670-468c-a687-5bab8a66cd3fJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/198a5082ea21ec80eb0a2a300046cd46c75c9d15/eventsJSON