Data Engineering built for HR Tech companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For HR Tech companies, this means navigating GDPR, EEOC guidelines (US) while shipping fast.
Who needs Data Engineering for HR Tech?
- Disconnected ATS, payroll and HRIS systems
- Compliance with multi-jurisdiction labor laws
- Low employee adoption of internal HR tools
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
HR software must serve both compliance teams and the employees who actually have to use it daily.
From Kathmandu, our team delivers Data Engineering for HR Tech businesses across with real timezone overlap.
See how GarudLabs can deliver Data Engineering for your team
Book a free 30-minute discovery callWhat HR Tech leaders in wish they knew before starting Data Engineering
- Disconnected ATS, payroll and HRIS systems
- Compliance with multi-jurisdiction labor laws
- Low employee adoption of internal HR tools
- Bias and fairness concerns in hiring algorithms
- Integrating background check and benefits providers
From discovery to deployment: our Data Engineering process for HR Tech
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:
- GDPR
- EEOC guidelines (US)
- Local labor law compliance
- SOC 2 for HR data handling
Proven Results
"We helped an HR platform reduce time-to-hire by 31% with automated candidate screening workflows."
Read the full case studyStop guessing on Data Engineering — let's build a real plan together
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 hr tech projects addressing challenges like disconnected ats, payroll and hris systems. We helped an HR platform reduce time-to-hire by 31% with automated candidate screening workflows.
For hr tech clients, we pay close attention to GDPR, EEOC guidelines (US), 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 hr tech clients include disconnected ats, payroll and hris systems and compliance with multi-jurisdiction labor laws. We tailor our discovery process to surface the specific version of these problems your business faces.