TL;DR

Data Engineer (Data Science/ML): Building and maintaining large-scale, high-quality data pipelines and backend systems that process billions of events daily with an accent on scalability, reliability, and performance. Focus on designing and operating complex big data pipelines, collaborating with multicultural teams, and implementing cutting-edge data technologies.

Location: Hybrid model blending home and in-office experiences in Bucharest

Company

%hirify_global% is a leader in commerce media, providing AI-powered advertising solutions to brands, agencies, and publishers worldwide, fostering an open and diverse work environment.

What you will do

Build and operate complex big data pipelines for ad campaign performance measurement.
Collaborate with multicultural R&D teams to ensure seamless communication between systems.
Explore and implement cutting-edge data technologies to enhance the platform.
Manage stakeholders and communicate complex data strategies effectively.
Contribute to and review technical design documents.
Continuously deploy applications focusing on efficiency and reliability.

Requirements

Location: Bucharest office with hybrid work model
3-5 years of experience in software development and building scalable data pipelines.
Proficiency in batch and streaming data engineering.
Strong experience with Spark, Flink, Scala, Python, and SQL dialects.
Positive, collaborative mindset and strong communication skills.
Experience working in Agile environments and delivering high-quality code.

Culture & Benefits

Hybrid work model combining home and office.
Learning, mentorship, and career development programs.
Health benefits, wellness perks, and mental health support.
Diverse, inclusive, and globally connected team.
Fair pay with performance-based rewards and potential equity.

Hiring process

HR interview to align expectations and answer questions.
Technical screen with live coding exercise.
In-depth coding interview developing features on a small web app.
System design interview focusing on scalable backend and fullstack systems.
Final behavioral and culture-focused interview with senior team members.