bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesColumbiauniversity1Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)

Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)

Columbiauniversity1 · New York, NY, United States · Active · $11,000–$13,000 / year · SmartRecruiters

Job facts

FieldValue
CompanyColumbiauniversity1
TitleAdjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)
Normalized title-
Department / teamApplied Analytics
LocationNew York, NY, United States
Work model-
Employment typePart Time
Salary$11,000–$13,000 / year
Statusactive
ATS providerSmartRecruiters
Posted / first seen2026-02-27 / 2026-05-31
Changed / last seen2026-05-31 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Columbiauniversity1.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through SmartRecruiters.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in New York.Open
Department jobsActive postings in Applied Analytics.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

CompanyColumbiauniversity1
Source252db8b6-df89-482b-953f-2d4f2f975720
ATS providerSmartRecruiters

Description

Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Columbia University’s  Master's i n Applied Analytics program seeks experienced industry professionals to serve as a part-time  L ecturer  for a graduate-level course in Managing Data. The Fundamentals of Data Engineering course provides students with a foundational context for managing data so that it can be leveraged and used with confidence. Analytic teams work closely with technology partners in managing data. Languages and techniques unique to each team can impede cooperation. To bridge this gap, this course provides a broad overview of data technology concepts including database engines and associated technologies and exposes students to foundational data principles, governance processes, and organizational prerequisites needed to overcome challenges to ensure data quality. Responsibilities Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions. Monitor and address student concerns and inquiries. Evaluate, grade student work and assessments. Conduct office hours. Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements Doctoral degree or equivalent required, in an area related to data science, statistics, computer science, or another discipline that provided rigorous training in quantitative analytics. Knowledge of databases, topics in Big Data, and Data Analysis. Knowledge of SQL and NoSQL databases. Knowledge of Python and Spark. 10+ years of related applied professional experience. Preferred Skills & Experience Knowledge of MapReduce strongly desired. Other software or programming languages like R and Tableau. Statistical and Machine learning knowledge. University teaching experience. Salary range:  $11,000 - $13,000 per semester long course Please submit a resume inclusive of university teaching experience. All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity Employer / Disability / Veteran

Full job record

Job ID4b419796cb9f797a851ba52bfc5f4271d0313272
Org ID223130e3-59f2-46de-a88c-89229a25e8c2
Source ID252db8b6-df89-482b-953f-2d4f2f975720
Board ID252db8b6-df89-482b-953f-2d4f2f975720
Providersmartrecruiters
Provider Job Key744000111908932
TitleAdjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)
Normalized Title
Statusactive
Activeyes
Location TextNew York, NY, United States
DepartmentApplied Analytics
Team
Employment Typepart_time
Workplace Type
Remote Policy
CountryUnited States
RegionNY
CityNew York
Salary RawColumbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society. The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good. Columbia University’s  Master's i n Applied Analytics program seeks experienced industry professionals to serve as a part-time  L ecturer  for a graduate-level course in Managing Data. The Fundamentals of Data Engineering course provides students with a foundational context for managing data so that it can be leveraged and used with confidence. Analytic teams work closely with technology partners in managing data. Languages and techniques unique to each team can impede cooperation. To bridge this gap, this course provides a broad overview of data technology concepts including database engines and associated technologies and exposes students to foundational data principles, governance processes, and organizational prerequisites needed to overcome challenges to ensure data quality. Responsibilities Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions. Monitor and address student concerns and inquiries. Evaluate, grade student work and assessments. Conduct office hours. Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. Requirements Doctoral degree or equivalent required, in an area related to data science, statistics, computer science, or another discipline that provided rigorous training in quantitative analytics. Knowledge of databases, topics in Big Data, and Data Analysis. Knowledge of SQL and NoSQL databases. Knowledge of Python and Spark. 10+ years of related applied professional experience. Preferred Skills & Experience Knowledge of MapReduce strongly desired. Other software or programming languages like R and Tableau. Statistical and Machine learning knowledge. University teaching experience. Salary range:  $11,000 - $13,000 per semester long course Please submit a resume inclusive of university teaching experience. All your information will be kept confidential according to EEO guidelines. Columbia University is an Equal Opportunity Employer / Disability / Veteran
Salary Min11,000
Salary Max13,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111908932-adjunct-lecturer-fundamentals-of-data-engineering-on-campus-fall-26-
Apply URLhttps://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111908932-adjunct-lecturer-fundamentals-of-data-engineering-on-campus-fall-26-?oga=true
First Seen At2026-05-31 17:36:11Z
Last Seen At2026-06-06 19:41:36Z
Last Checked At2026-06-06 19:41:36Z
Last Changed At2026-05-31 17:36:11Z
Inactive At
Source Posted At2026-02-27 17:54:49Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=smartrecruiters/board=columbiauniversity1/date=2026-06-06/2026-06-06T19-41-30-851Z-20a34eae43ceee4fdc40a938c901dd77121f850d242397beae458f49d7707da8.json
Event Fields
{
  "content_hash": "1512b0c4cb84b18e7a4cc0d3e7a38ac3b6158f673f150af06be98a0f2a67460a",
  "source_hash": "f90856774a6c64d35e6db72925715f99ea933ac415d31e2e5c0cd6615788885d",
  "last_changed_at": "2026-05-31T17:36:11.977Z",
  "active_status": "active"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "New York, NY, United States",
    "city": "New York",
    "region": "NY",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.8
  },
  "salary_max": 13000,
  "salary_min": 11000,
  "inferred_at": "2026-06-06T19:41:36.098Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "New York, NY, United States",
      "city": "New York",
      "region": "NY",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.8
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": "year",
  "workplace_type": null,
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "id": "744000111908932",
  "ref": "https://api.smartrecruiters.com/v1/companies/columbiauniversity1/postings/744000111908932",
  "name": "Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)",
  "uuid": "3e889d59-4211-48da-913f-54470cee759b",
  "detail": {
    "id": "744000111908932",
    "name": "Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)",
    "uuid": "3e889d59-4211-48da-913f-54470cee759b",
    "jobAd": {
      "sections": {
        "jobDescription": {
          "text": "<p>Columbia University’s&#xa0;<a href=\"https://sps.columbia.edu/academics/masters/nonprofit-management\">Master's i</a><a href=\"https://sps.columbia.edu/academics/masters/applied-analytics\">n Applied Analytics</a> program seeks&#xa0;experienced industry professionals to serve as a part-time&#xa0;<a href=\"https://c.smartrecruiters.com/sr-company-attachments-prod-dc5/5a94164be4b009bfee282818/e5983b2c-ecbd-48d4-b4fb-c89dbe4d150b?r=s3-eu-central-1\">L</a><a href=\"https://c.smartrecruiters.com/sr-company-attachments-prod-dc5/5a94164be4b009bfee282818/0afe4fbd-5824-4db6-b33c-6708cfac80fe?r=s3-eu-central-1\">ecturer</a>&#xa0;for a graduate-level course in Managing Data.&#xa0;</p><p>The Fundamentals of Data Engineering course provides students with a foundational context for managing data so that it can be leveraged and used with confidence. Analytic teams work closely with technology partners in managing data. Languages and techniques unique to each team can impede cooperation. To bridge this gap, this course provides a broad overview of data technology concepts including database engines and associated technologies and exposes students to foundational data principles, governance processes, and organizational prerequisites needed to overcome challenges to ensure data quality.&#xa0;</p><p><strong><em>Responsibilities</em></strong></p><ul><li><p>Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions.</p></li><li><p>Monitor and address student concerns and inquiries.</p></li><li><p>Evaluate, grade student work and assessments.</p></li><li><p>Conduct office hours.</p></li></ul><ul></ul>",
          "title": "Job Description"
        },
        "qualifications": {
          "text": "<p><strong>Columbia University SPS </strong>operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.&#xa0;</p><p><strong>Requirements</strong></p><ul><li><p>Doctoral degree or equivalent required, in an area related to data science, statistics, computer science, or another discipline that provided rigorous training in quantitative analytics.</p></li><li><p>Knowledge of databases, topics in Big Data, and Data Analysis.</p></li><li><p>Knowledge of SQL and NoSQL databases.</p></li><li><p>Knowledge of Python and Spark.</p></li><li><p>10+ years of related applied professional experience.</p></li></ul><p><strong>Preferred Skills &amp; Experience</strong></p><ul><li><p>Knowledge of MapReduce strongly desired.</p></li><li><p>Other software or programming languages like R and Tableau.</p></li><li><p>Statistical and Machine learning knowledge.</p></li><li><p>University teaching experience.</p></li></ul>",
          "title": "Qualifications"
        },
        "companyDescription": {
          "text": "<p><strong>Columbia University </strong>has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society.</p><p><strong>The School of Professional Studies at Columbia University </strong>offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.</p>",
          "title": "Company Description"
        },
        "additionalInformation": {
          "text": "<p><strong>Salary range:</strong>&#xa0;$11,000 - $13,000 per semester long course<br>\n<br>\nPlease submit a resume inclusive of university teaching experience.</p><p><em><strong>All your information will be kept confidential according to EEO guidelines.</strong></em></p><p><strong><em>Columbia University is an Equal Opportunity Employer / Disability / Veteran</em></strong></p>",
          "title": "Additional Information"
        }
      }
    },
    "jobId": "1b18fc28-5221-43c1-b385-045df2639c7b",
    "active": true,
    "company": {
      "name": "Columbia University",
      "identifier": "ColumbiaUniversity1"
    },
    "creator": {
      "name": "",
      "avatarUrl": ""
    },
    "jobAdId": "701c081a-3940-42e5-a3f8-4e9c56777aaa",
    "applyUrl": "https://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111908932-adjunct-lecturer-fundamentals-of-data-engineering-on-campus-fall-26-?oga=true",
    "function": {
      "id": "administrative",
      "label": "Administrative"
    },
    "industry": {
      "id": "higher_education",
      "label": "Higher Education"
    },
    "language": {
      "code": "en",
      "label": "English",
      "labelNative": "English (US)"
    },
    "location": {
      "city": "New York",
      "hybrid": false,
      "region": "NY",
      "remote": false,
      "country": "us",
      "latitude": "40.7127753",
      "longitude": "-74.0059728",
      "fullLocation": "New York, NY, United States"
    },
    "refNumber": "REF1296Y",
    "department": {
      "id": 1068780,
      "label": "Applied Analytics"
    },
    "postingUrl": "https://jobs.smartrecruiters.com/ColumbiaUniversity1/744000111908932-adjunct-lecturer-fundamentals-of-data-engineering-on-campus-fall-26-",
    "visibility": "PUBLIC",
    "customField": [
      {
        "fieldId": "5fff0898d102e3515e48905d",
        "fieldLabel": "Course Number",
        "valueLabel": "5400"
      },
      {
        "fieldId": "5ad88b18b60a5e486a2d9efa",
        "valueId": "3bbef67b-e16f-420a-a14b-df988359c43f",
        "fieldLabel": "Employee Job Category",
        "valueLabel": "Faculty Job"
      },
      {
        "fieldId": "5ad9ffd26d8bc56863dd9b7a",
        "valueId": "a01a9441-a122-48d3-8407-45f2155e4fd4",
        "fieldLabel": "Term",
        "valueLabel": "2026 FALL"
      },
      {
        "fieldId": "COUNTRY",
        "valueId": "us",
        "fieldLabel": "Country/Region",
        "valueLabel": "United States"
      },
      {
        "fieldId": "5a945d216d8bc505a492dc8e",
        "valueId": "default",
        "fieldLabel": "Brands",
        "valueLabel": "Columbia University"
      },
      {
        "fieldId": "5abbec096d8bc56863dd96eb",
        "valueId": "1810e6b8-0f96-4fca-b8e7-a84906e7146e",
        "fieldLabel": "Role",
        "valueLabel": "Lecturer, Part-time"
      },
      {
        "fieldId": "5a945d216d8bc505a492dc8f",
        "valueId": "1068780",
        "fieldLabel": "Department",
        "valueLabel": "Applied Analytics"
      },
      {
        "fieldId": "5ab2b7b9b60a5e2f7b2c5b2e",
        "valueId": "9a8ca717-4cdc-408a-a528-a1d282c58b19",
        "fieldLabel": "Division",
        "valueLabel": "Masters"
      },
      {
        "fieldId": "5ab2b7766d8bc519b1d9db9d",
        "valueId": "ce0cf7f9-c606-43be-b2ea-374fac2c7fd7",
        "fieldLabel": "Program",
        "valueLabel": "Applied Analytics"
      },
      {
        "fieldId": "5ada008db60a5e486a2d9f4b",
        "valueId": "0c6291f7-c010-4b09-9d2a-5471b248fb56",
        "fieldLabel": "Academic Program",
        "valueLabel": "APAN"
      },
      {
        "fieldId": "5ab3bcdab60a5e2f7b2c5b5c",
        "valueId": "6b516b3e-9a6c-4f1e-8591-f59a3aa5b980",
        "fieldLabel": "Course Modality",
        "valueLabel": "On Campus"
      },
      {
        "fieldId": "6005f3a3e57517446f4f2d3b",
        "fieldLabel": "Section Number",
        "valueLabel": "001"
      }
    ],
    "referralUrl": "https://jobs.smartrecruiters.com/external-referrals/company/ColumbiaUniversity1/publication/3e889d59-4211-48da-913f-54470cee759b?dcr_ci=ColumbiaUniversity1",
    "defaultJobAd": true,
    "releasedDate": "2026-02-27T17:54:49.070Z",
    "experienceLevel": {
      "id": "mid_senior_level",
      "label": "Mid-Senior Level"
    },
    "typeOfEmployment": {
      "id": "part-time",
      "label": "Part-time"
    }
  },
  "company": {
    "name": "Columbia University",
    "identifier": "ColumbiaUniversity1"
  },
  "jobAdId": "701c081a-3940-42e5-a3f8-4e9c56777aaa",
  "function": {
    "id": "administrative",
    "label": "Administrative"
  },
  "industry": {
    "id": "higher_education",
    "label": "Higher Education"
  },
  "language": {
    "code": "en",
    "label": "English",
    "labelNative": "English (US)"
  },
  "location": {
    "city": "New York",
    "hybrid": false,
    "region": "NY",
    "remote": false,
    "country": "us",
    "latitude": "40.7127753",
    "longitude": "-74.0059728",
    "fullLocation": "New York, NY, United States"
  },
  "refNumber": "REF1296Y",
  "department": {
    "id": "1068780",
    "label": "Applied Analytics"
  },
  "visibility": "PUBLIC",
  "customField": [
    {
      "fieldId": "5ad88b18b60a5e486a2d9efa",
      "valueId": "3bbef67b-e16f-420a-a14b-df988359c43f",
      "fieldLabel": "Employee Job Category",
      "valueLabel": "Faculty Job"
    },
    {
      "fieldId": "5ad9ffd26d8bc56863dd9b7a",
      "valueId": "a01a9441-a122-48d3-8407-45f2155e4fd4",
      "fieldLabel": "Term",
      "valueLabel": "2026 FALL"
    },
    {
      "fieldId": "COUNTRY",
      "valueId": "us",
      "fieldLabel": "Country/Region",
      "valueLabel": "United States"
    },
    {
      "fieldId": "5a945d216d8bc505a492dc8e",
      "valueId": "default",
      "fieldLabel": "Brands",
      "valueLabel": "Columbia University"
    },
    {
      "fieldId": "5abbec096d8bc56863dd96eb",
      "valueId": "1810e6b8-0f96-4fca-b8e7-a84906e7146e",
      "fieldLabel": "Role",
      "valueLabel": "Lecturer, Part-time"
    },
    {
      "fieldId": "5a945d216d8bc505a492dc8f",
      "valueId": "1068780",
      "fieldLabel": "Department",
      "valueLabel": "Applied Analytics"
    },
    {
      "fieldId": "5ab2b7b9b60a5e2f7b2c5b2e",
      "valueId": "9a8ca717-4cdc-408a-a528-a1d282c58b19",
      "fieldLabel": "Division",
      "valueLabel": "Masters"
    },
    {
      "fieldId": "5ab2b7766d8bc519b1d9db9d",
      "valueId": "ce0cf7f9-c606-43be-b2ea-374fac2c7fd7",
      "fieldLabel": "Program",
      "valueLabel": "Applied Analytics"
    },
    {
      "fieldId": "5ada008db60a5e486a2d9f4b",
      "valueId": "0c6291f7-c010-4b09-9d2a-5471b248fb56",
      "fieldLabel": "Academic Program",
      "valueLabel": "APAN"
    },
    {
      "fieldId": "5ab3bcdab60a5e2f7b2c5b5c",
      "valueId": "6b516b3e-9a6c-4f1e-8591-f59a3aa5b980",
      "fieldLabel": "Course Modality",
      "valueLabel": "On Campus"
    },
    {
      "fieldId": "5fff0898d102e3515e48905d",
      "fieldLabel": "Course Number",
      "valueLabel": "5400"
    },
    {
      "fieldId": "6005f3a3e57517446f4f2d3b",
      "fieldLabel": "Section Number",
      "valueLabel": "001"
    }
  ],
  "defaultJobAd": true,
  "releasedDate": "2026-02-27T17:54:49.070Z",
  "detail_errors": [],
  "experienceLevel": {
    "id": "mid_senior_level",
    "label": "Mid-Senior Level"
  },
  "typeOfEmployment": {
    "id": "part-time",
    "label": "Part-time"
  }
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/4b419796cb9f797a851ba52bfc5f4271d0313272?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/223130e3-59f2-46de-a88c-89229a25e8c2JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/252db8b6-df89-482b-953f-2d4f2f975720JSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/4b419796cb9f797a851ba52bfc5f4271d0313272/eventsJSON