File size: 5,069 Bytes
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standardize job title, employment type, location, company (department still figuring out how to standardize)
salary min and max format is edited to ensure able to become INT type
flag potential duplicate jobs
*/
WITH standardized_jobs AS (
SELECT
source,
job_id,
search_term,
url,
collection_timestamp,
job_title AS job_title_raw,
-- standardize job_title
CASE
WHEN job_title ILIKE '%Data Analyst%' THEN 'Data Analyst'
WHEN job_title ILIKE '%Data Analytic%' THEN 'Data Analyst'
WHEN job_title ILIKE '%Data Engineer%' THEN 'Data Engineer'
WHEN job_title ILIKE '%Data Scientist%' THEN 'Data Scientist'
WHEN job_title ILIKE '%Data Science%' THEN 'Data Scientist'
WHEN job_title ILIKE '%AI Engineer%' THEN 'AI Engineer'
WHEN job_title ILIKE '%Machine Learning Engineer%' THEN 'ML Engineer'
WHEN job_title ILIKE '%ML Engineer%' THEN 'ML Engineer'
WHEN job_title ILIKE '%data warehouse developer%' THEN 'Data Warehouse Developer'
WHEN job_title ILIKE '%database administrator%' THEN 'Database Administrator'
WHEN job_title ILIKE '%finance analyst%' THEN 'Finance Analyst'
WHEN job_title ILIKE '%business intelligence analyst%' THEN 'BI Analyst'
WHEN job_title ILIKE '%bi analyst%' THEN 'BI Analyst'
WHEN job_title ILIKE '%bi developer%' THEN 'BI Developer'
WHEN job_title ILIKE '%business analyst%' THEN 'Business Analyst'
WHEN job_title ILIKE '%analytics engineer%'THEN 'Analytics Engineer'
ELSE job_title
END AS job_title_standardized,
-- standardize company names
CASE
WHEN company ILIKE '%pwc%' THEN 'PwC Malaysia'
WHEN company ILIKE '%hong leong%' THEN 'Hong Leong'
WHEN company ILIKE '%luxoft%' THEN 'Luxoft'
WHEN company ILIKE '%accenture%' THEN 'Accenture'
WHEN company ILIKE '%shopee%' THEN 'Shopee'
WHEN company ILIKE '%uob%' THEN 'UOB'
WHEN company ILIKE '%maybank%' THEN 'Maybank'
WHEN company ILIKE '%aia%' THEN 'AIA'
WHEN company ILIKE '%ocbc%' THEN 'OCBC'
WHEN company ILIKE '%alliance bank%' THEN 'Alliance Bank'
WHEN company ILIKE '%deloitte%' THEN 'Deloitte'
ELSE company
END AS company,
-- standardize locations
CASE
WHEN location ILIKE '%kuala lumpur%' THEN 'Kuala Lumpur'
ELSE split_part(location, ',', 1)
END AS location,
-- standardize employement type
CASE
WHEN job_title ILIKE '%intern%' THEN 'Internship'
WHEN employment_type ILIKE '%full%time%' THEN 'Full-time'
WHEN employment_type ILIKE '%part%time%' THEN 'Part-time'
WHEN employment_type ILIKE '%contract%' THEN 'Contract'
ELSE employment_type
END AS employment_type,
-- no changes for now to department
department,
-- edit salary min to reflect correctly
CAST(
CASE
WHEN salary_min LIKE 'RM%–%per month'
THEN NULLIF(TRIM(REPLACE(REPLACE(RIGHT(split_part(salary_min, '–', 1), -3), ',', ''), chr(160), '')), '')
ELSE NULL
END AS INTEGER
) AS salary_min,
-- edit salary max to reflect correctly
CAST(
CASE
WHEN salary_max LIKE 'RM%–%per month'
THEN NULLIF(TRIM(REPLACE(REPLACE(LEFT(RIGHT(split_part(salary_max, '–', -1), -3), -10), ',', ''), chr(160), '')), '')
ELSE NULL
END AS INTEGER
) AS salary_max,
CAST(posting_date AS DATE),
job_description
FROM stg_jobs
)
INSERT INTO silver_jobs (
source,
job_id,
search_term,
url,
collection_timestamp,
job_title_raw,
job_title_standardized,
company,
location,
duplicate_status,
employment_type,
department,
salary_min,
salary_max,
posting_date,
job_description
)
SELECT
source,
job_id,
search_term,
url,
collection_timestamp,
job_title_raw,
job_title_standardized,
company,
location,
CASE
-- Same source, same standardized job details
WHEN COUNT(*) OVER (
PARTITION BY
source,
company,
job_title_raw,
location
) > 1
THEN 'Potential Duplicate'
-- Same job characteristics, but listed on different websites
WHEN COUNT(*) OVER (
PARTITION BY
company,
job_title_raw,
location
) > 1
THEN 'Cross-source Match'
ELSE 'Unique'
END AS duplicate_status,
employment_type,
department,
salary_min,
salary_max,
posting_date,
job_description
FROM standardized_jobs;
ON CONFLICT
DO NOTHING;
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