HR Analytics Engineer: AI-Driven Data Pipelines & Dashboards

United States Digital Space LLC; United States; Remote; USD 90,000 - 150,000; Full time

Benefits offered by this job

Health coverage for you and family

Flexible locations and schedules

Generous vacation days

Volunteer time allowance

Parental leave

Job summary

United States Digital Space LLC is seeking a hands-on Analytics Engineer to build and maintain HR data pipelines on our GCP/BigQuery/dbt data model with an AI-powered analytics layer. You will collaborate with the data scientist and HR leaders to stand up recruiting reporting as the first production use case on the new stack.

Your mission is to move the organization toward self-service analytics, delivering decision-ready insights to senior stakeholders across time zones and geographies.

Qualifications

• 2+ years of hands-on experience building and maintaining data pipelines in Google Cloud Platform (GCP).
• Strong SQL and Python skills.
• Direct experience extracting and modeling data from at least one major HRIS or ATS platform via its reporting or API layer.

Responsibilities

• Build and maintain HR data pipelines linking data across the employee lifecycle (Workday, Greenhouse, Qualtrics, ServiceNow).
• Develop scalable, self-service dashboards in BI tools or code-based environments.
• Implement data governance practices for sensitive HR and compensation data.
• Automate recruiting reports and translate talent data into actionable insights.
• Monitor data quality and establish a single version of truth across systems.

Skills

GCP

SQL

Python

Data pipelines

HRIS/ATS integration

Tools

Looker

Tableau

BigQuery

dbt

Job description

United States Digital Space LLC is seeking a hands-on Analytics Engineer to build and maintain HR data pipelines on our GCP/BigQuery/dbt data model with an AI-powered analytics layer. You will collaborate with the data scientist and HR leaders to stand up recruiting reporting as the first production use case on the new stack.

Your mission is to move the organization toward self-service analytics, delivering decision-ready insights to senior stakeholders across time zones and geographies.