TL;DR

Sr. Data Engineer (Data platform): Designing and building %hirify_global%'s next-generation data platform that powers analytics, experimentation, and AI-driven product features used by millions of users with an accent on architecting and maintaining infrastructure for delivering data. Focus on data services optimized for traditional analytics and emerging GenAI/ML workloads.

Location: Must live in or be willing to relocate to one of the following states to be eligible for hire: Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Louisiana, Massachusetts, Michigan, Minnesota, New York, New Jersey, North Carolina, Pennsylvania, Texas, Vermont, Virginia, Washington.

Salary: $132,145 - $181,699 USD

Company

%hirify_global% is the world’s leading Connections Platform, empowering businesses to create memorable connections with their customers at every physical and digital touchpoint.

What you will do

Build well-tested, well-documented data services and improve existing ones—optimized for both traditional analytics and emerging GenAI/ML workloads.
Create pipelines to move and transform data efficiently and design flexible internal and external APIs to expose our data.
Establish and enforce architectural and data quality standards, including monitoring, observability, and governance frameworks.
Collaborate effectively with cross-functional leaders to ensure on-time delivery of key initiatives.
Support our internal teams in maintaining and designing user tracking events.
Mentor other engineers on best practices and implementation approaches and champion a culture of continuous learning, technical rigor, and AI-first engineering practices.

Requirements

You have hands-on experience in data engineering on cloud platforms (GCP preferred), with focus on cost and performance optimization.
You are adept at clearly communicating technical concepts to engineers and cross-functional stakeholders.
You are an expert in SQL and Python, with deep experience in data modeling, optimization, and reusable frameworks.
You have proven track record with modern data stack: orchestration (Airflow), transformation (dbt), streaming (Beam/Spark), and data processing (Dataflow).
You are experienced in data platform operations: containerization (Docker/Kubernetes), CI/CD pipelines, and data governance.
You are familiar with modern data paradigms such as lakehouse architectures, event-driven systems, and AI-centric data tooling.

Nice to have

Understanding of infrastructure-as-code (Terraform) and backend service development (Go).

Culture & Benefits

Inclusive health, dental, and vision plans built to support diverse lifestyles.
Generous paid parental leave.
Robust mental health support and Employee Assistance Program (EAP) with confidential counseling services.
Flexible PTO policy and company breaks.
401k with up to 4% employer match.
Flexible workspace support provided, including home office, cell phone and WiFi service reimbursement.