Data Engineering built for Recruitment Tech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Recruitment Tech companies, this means navigating EEOC guidelines (US), GDPR while shipping fast.
Who needs Data Engineering for Recruitment Tech?
- Long time-to-hire driven by manual screening
- Candidate experience suffering from clunky application flows
- Integrating ATS with assessment and background check tools
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Hiring platforms succeed when they actually shorten the painful gap between job post and signed offer.
From Kathmandu, our team delivers Data Engineering for Recruitment Tech businesses across with real timezone overlap.
Stop guessing on Data Engineering — let's build a real plan together
Book a free 30-minute discovery callCommon Data Engineering mistakes we see across Recruitment Tech teams in
- Long time-to-hire driven by manual screening
- Candidate experience suffering from clunky application flows
- Integrating ATS with assessment and background check tools
- Bias concerns in automated candidate scoring
- Sourcing quality candidates at scale
How GarudLabs approaches Data Engineering for Recruitment Tech companies in
Data warehouse architecture (Snowflake, BigQuery)
ETL/ELT pipeline development
Data quality monitoring and alerting
BI dashboard integration
Data governance and access controls
Core Technology Stack
SnowflakeBigQueryAirflowdbtPythonKafkaAWS Glue
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $140,000
Data Engineering engagements in this combination typically need to account for:
- EEOC guidelines (US)
- GDPR
- Local labor law compliance
- Background check regulations
Proven Results
"We helped a recruitment platform cut time-to-hire by 35% with AI-assisted candidate matching."
Read the full case studyLet's scope your Data Engineering project — book a free call today
Get a free project cost estimateFrequently Asked Questions
Most Data Engineering engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Data Engineering projects with us typically range from $25,000 - $140,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For data engineering, we typically work with Snowflake, BigQuery, Airflow, dbt, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical data engineering engagement includes data warehouse architecture (snowflake, bigquery), along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for data engineering because of data scattered across disconnected systems, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple recruitment tech projects addressing challenges like long time-to-hire driven by manual screening. We helped a recruitment platform cut time-to-hire by 35% with AI-assisted candidate matching.
For recruitment tech clients, we pay close attention to EEOC guidelines (US), GDPR, building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for recruitment tech clients include long time-to-hire driven by manual screening and candidate experience suffering from clunky application flows. We tailor our discovery process to surface the specific version of these problems your business faces.