About the Role

We are expanding our Data & AI team and looking for a skilled Data Engineer with a strong Python backend background who has transitioned into data engineering. This role is ideal for someone who started as a backend developer (Python) and has at least 1+ year of hands-on data engineering experience, now aiming to grow further in this domain.

You will work closely with our current Data Engineer and AI Engineer to build scalable data platforms, pipelines, and services. This is a high-autonomy position within a young team where you’ll influence data infrastructure decisions, design systems from scratch, and help shape our data-driven foundation.

Key Responsibilities

Design, build, and maintain data pipelines and services to support analytics, ML, and AI solutions.
Work with distributed systems, optimize data processing, and handle large-scale data workloads.
Collaborate with AI Engineers to support model integration (backend support for ML models, not full deployment responsibility).
Design solutions for vague or high-level business requirements with strong problem-solving skills.
Contribute to building a scalable data platform and help set best practices for data engineering in the company.
Participate in rapid prototyping (PoCs and MVPs), deploying early solutions, and iterating quickly.

Requirements

4 years of professional experience (with at least 1 year dedicated to data engineering).
Strong Python backend development experience (service creation, APIs).
Good understanding of data processing concepts, distributed systems, and system evolution.
Experience with cloud platforms (AWS preferred, GCP acceptable).
Familiarity with Docker and containerized environments.
Experience with Spark, Kubernetes, and optimization of high-load systems.
Ability to handle loosely defined requirements, propose solutions, and work independently.
A proactive mindset – technical initiatives tied to business impact are highly valued.
English sufficient to read technical documentation (working language: Ukrainian/Russian).

Nice-to-Haves

Exposure to front-end development (JavaScript/TypeScript) – not required, but a plus.
Experience with scalable data architectures, stream processing, and data modeling.
Understanding of the business impact of technical optimizations.

Team & Process

You’ll join a growing Data & AI department responsible for data infrastructure, AI agents, and analytics systems.
Two interview stages:
Technical Interview (Python & Data Engineering focus).
Cultural Fit Interview (expectations, career growth, alignment).
Autonomy and decision-making freedom in a small, fast-moving team.