Field reference: People DB

All 36 fields of the People DB, grouped by category. Names are the Parquet field names; the CSV delivery uses its own column headers, listed under CSV column names.

Every field may be null unless marked required. Today specter_person_id is guaranteed.

Under each type is the column’s Parquet type, as DuckDB names it: VARCHAR is a string, BIGINT a 64-bit integer, DOUBLE a 64-bit float, and [] a list. Each category ends with its full Parquet schema, ready to copy.

What’s in it

Category	Fields
ID	3
Timestamp	1
Status	1
Personal	14
Experience	7
Company Data	7
Education	1
Social Engagement	2

ID

Field	Type	Description
`specter_person_id`	`string` required `VARCHAR`	Specter identifier for the person. Resolves against the People DB.
`specter_talent_signal_ids`	`array<string>` `VARCHAR[]`	All Talent Signals IDs for this profile.
`specter_strategic_signal_ids`	`array<string>` `VARCHAR[]`	All Investor Interest Signals IDs for this profile.

Parquet schema: ID

(
  specter_person_id             VARCHAR,
  specter_talent_signal_ids     VARCHAR[],
  specter_strategic_signal_ids  VARCHAR[]
)

Timestamp

Field	Type	Description
`last_updated`	`timestamp` `TIMESTAMP`	Timestamp of latest update for the profile in text format.

Parquet schema: Timestamp

Timestamp

(
  last_updated  TIMESTAMP
)

Status

Field	Type	Description
`status`	`string` `VARCHAR`	Whether the profile was added or updated. One of `added`, `updated`.

Parquet schema: Status

Status

(
  status  VARCHAR
)

Personal

Field	Type	Description
`profile_picture`	`string` `VARCHAR`	URL of the person’s profile picture.
`first_name`	`string` `VARCHAR`	First name of the person.
`last_name`	`string` `VARCHAR`	Last name of the person.
`full_name`	`string` `VARCHAR`	Full name of the person.
`linkedin_url`	`string` `VARCHAR`	URL of the person’s LinkedIn profile.
`linkedin_num_id`	`integer` `BIGINT`	LinkedIn numeric ID.
`linkedin_urn`	`string` `VARCHAR`	LinkedIn’s own numeric identifier for the profile.
`twitter_url`	`string` `VARCHAR`	URL of the person’s X (Twitter) profile.
`github_url`	`string` `VARCHAR`	GitHub profile URL.
`about`	`string` `VARCHAR`	Brief biography of the person.
`tagline`	`string` `VARCHAR`	The person’s professional tagline.
`location`	`string` `VARCHAR`	Person location (city level)
`region`	`string` `VARCHAR`	Person region (continent level)
`people_highlights`	`array<string>` `VARCHAR[]`	Highlights are awarded tags to people reflecting specific and different growth patterns.

Parquet schema: Personal

Personal

(
  profile_picture    VARCHAR,
  first_name         VARCHAR,
  last_name          VARCHAR,
  full_name          VARCHAR,
  linkedin_url       VARCHAR,
  linkedin_num_id    BIGINT,
  linkedin_urn       VARCHAR,
  twitter_url        VARCHAR,
  github_url         VARCHAR,
  about              VARCHAR,
  tagline            VARCHAR,
  location           VARCHAR,
  region             VARCHAR,
  people_highlights  VARCHAR[]
)

Experience

Field	Type	Description
`level_of_seniority`	`string` `VARCHAR`	Seniority of the person’s current role.
`years_of_experience`	`integer` `INTEGER`	Total years of professional experience.
`education_level`	`string` `VARCHAR`	Highest level of education attained.
`current_tenure`	`integer` `INTEGER`	Duration of the current role in months.
`average_tenure`	`integer` `INTEGER`	Average duration of past roles in months.
`languages`	`array<object>` `STRUCT(…)[]`	Languages spoken by the person.
↳ `name`	`string` `VARCHAR`
↳ `proficiency_level`	`string` `VARCHAR`
`skills`	`array<string>` `VARCHAR[]`	List of skills possessed by the person.

Parquet schema: Experience

Experience

(
  level_of_seniority   VARCHAR,
  years_of_experience  INTEGER,
  education_level      VARCHAR,
  current_tenure       INTEGER,
  average_tenure       INTEGER,
  languages            STRUCT(
    name VARCHAR,
    proficiency_level VARCHAR
  )[],
  skills               VARCHAR[]
)

Company Data

Field	Type	Description
`experience`	`array<object>` `STRUCT(…)[]`	List of job experiences.
↳ `company_name`	`string` `VARCHAR`
↳ `specter_company_id`	`string` `VARCHAR`
↳ `domain`	`string` `VARCHAR`
↳ `linkedin_url`	`string` `VARCHAR`
↳ `description`	`string` `VARCHAR`
↳ `company_size`	`string` `VARCHAR`
↳ `specter_industry`	`array<string>` `VARCHAR[]`
↳ `specter_tech_verticals`	`array<array<string>>` `VARCHAR[][]`
↳ `title`	`string` `VARCHAR`
↳ `is_founder`	`boolean` `BOOLEAN`
↳ `departments`	`array<string>` `VARCHAR[]`
↳ `start_date`	`date` `DATE`
↳ `end_date`	`date` `DATE`
↳ `location`	`string` `VARCHAR`
↳ `is_current`	`boolean` `BOOLEAN`
↳ `founded_year`	`integer` `INTEGER`
↳ `job_order`	`integer` `INTEGER`
`current_position_title`	`string` `VARCHAR`	Title of the current and latest job role.
`current_position_company_name`	`string` `VARCHAR`	Name of the company where the person currently works (latest only)
`current_position_company_website`	`string` `VARCHAR`	Website of the latest current employer.
`past_position_title`	`string` `VARCHAR`	Title of the latest past position.
`past_position_company_name`	`string` `VARCHAR`	Name of company of the latest past position.
`past_position_company_website`	`string` `VARCHAR`	Website of the company of the latest past position.

Parquet schema: Company Data

Company Data

(
  experience                        STRUCT(
    company_name VARCHAR,
    specter_company_id VARCHAR,
    domain VARCHAR,
    linkedin_url VARCHAR,
    description VARCHAR,
    company_size VARCHAR,
    specter_industry VARCHAR[],
    specter_tech_verticals VARCHAR[][],
    title VARCHAR,
    is_founder BOOLEAN,
    departments VARCHAR[],
    start_date DATE,
    end_date DATE,
    location VARCHAR,
    is_current BOOLEAN,
    founded_year INTEGER,
    job_order INTEGER
  )[],
  current_position_title            VARCHAR,
  current_position_company_name     VARCHAR,
  current_position_company_website  VARCHAR,
  past_position_title               VARCHAR,
  past_position_company_name        VARCHAR,
  past_position_company_website     VARCHAR
)

Education

Field	Type	Description
`education`	`array<object>` `STRUCT(…)[]`	List of educational qualifications.
↳ `name`	`string` `VARCHAR`
↳ `linkedin_url`	`string` `VARCHAR`
↳ `field_of_study`	`string` `VARCHAR`
↳ `degree_title`	`string` `VARCHAR`
↳ `description`	`string` `VARCHAR`
↳ `start_date`	`date` `DATE`
↳ `end_date`	`date` `DATE`
↳ `location`	`string` `VARCHAR`

Parquet schema: Education

Education

(
  education  STRUCT(
    name VARCHAR,
    linkedin_url VARCHAR,
    field_of_study VARCHAR,
    degree_title VARCHAR,
    description VARCHAR,
    start_date DATE,
    end_date DATE,
    location VARCHAR
  )[]
)

Field	Type	Description
`linkedin_followers`	`integer` `INTEGER`	Number of followers on LinkedIn.
`linkedin_connections`	`integer` `INTEGER`	Number of connections on LinkedIn.

CSV column names

The CSV delivery carries the same fields under the headers below. Parquet, JSONL and the API all use the field name.

Field	CSV column
`specter_person_id`	Specter - Person ID
`specter_talent_signal_ids`	Specter - Talent Signal IDs
`specter_strategic_signal_ids`	Specter - Strategic Signal IDs
`last_updated`	Last Updated
`status`	Status
`profile_picture`	Profile Picture
`first_name`	First Name
`last_name`	Last Name
`full_name`	Full Name
`linkedin_url`	LinkedIn - URL
`linkedin_num_id`	LinkedIn - Num ID
`linkedin_urn`	LinkedIn - URN
`twitter_url`	Twitter - URL
`github_url`	GitHub - URL
`about`	About
`tagline`	Tagline
`location`	Location
`region`	Region
`people_highlights`	People Highlights
`level_of_seniority`	Level of Seniority
`years_of_experience`	Years of Experience
`education_level`	Education Level
`experience`	Experience
`current_position_title`	Current Position Title
`current_position_company_name`	Current Position Company Name
`current_position_company_website`	Current Position Company Website
`past_position_title`	Past Position Title
`past_position_company_name`	Past Position Company Name
`past_position_company_website`	Past Position Company Website
`current_tenure`	Current Tenure
`average_tenure`	Average Tenure
`education`	Education
`languages`	Languages
`skills`	Skills
`linkedin_followers`	LinkedIn - Followers
`linkedin_connections`	LinkedIn - Connections

Get started

Core data

Signals

Field reference: People DB

What’s in it

ID

Timestamp

Status

Personal

Experience

Company Data

Education

CSV column names

​What’s in it

​ID

​Timestamp

​Status

​Personal

​Experience

​Company Data

​Education

​Social Engagement

​CSV column names

What’s in it

ID

Timestamp

Status

Personal

Experience

Company Data

Education

Social Engagement

CSV column names