Job description
Description
Hello, let’s meet!
Who We Are
While Xebia is a global tech company, in Poland, our roots came from two teams – PGS Software, known for world-class cloud and software solutions, and GetInData, a pioneer in Big Data. Today, we’re a team of 1,000+ experts delivering top-notch work across cloud, data, and software. And we’re just getting started.
What We Do
We work on projects that matter – and that make a difference. From fintech and e-commerce to aviation, logistics, media, and fashion, we help our clients build scalable platforms, data-driven solutions, and next-gen apps using ML, LLMs, and Generative AI. Our clients include Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, and Allegro or InPost.
We value smart tech, real ownership, and continuous growth. We use modern, open-source stacks, and we’re proud to be trusted partners of Databricks, dbt, Snowflake, Azure, GCP, and AWS. Fun fact: we were the first AWS Premier Partner in Poland!
Beyond Projects
What makes Xebia special? Our community. We run events like the Data&AI Warsaw Summit, organize meetups (Software Talks, Data Tech Talks), and have a culture that actively support your growth via Guilds, Labs, and personal development budgets — for both tech and soft skills. It’s not just a job. It’s a place to grow.
What sets us apart?
Our mindset. Our vibe. Our people. And while that’s hard to capture in text – come visit us and see for yourself.
You will be:
designing, building and optimizing the data ingestion pipeline to reliably deliver billions of events daily in defined SLA,
leading initiatives to improve scalability, performance and reliability,
providing support for all product teams in building and optimizing their complex pipelines,
identifying and addressing pain points in the existing data platform; proposing and implementing high-leverage improvements,
developing new tools and frameworks to streamline the data platform workflows,
driving adoption of best practices in data and software engineering (testing, CI/CD, version control, monitoring),
working in close collaboration with data scientists and data analysts to help support their work in production,
supporting production ML workflows and real-time streaming use cases,
mentoring other engineers and contributing to a culture of technical excellence and knowledge sharing.
Requirements
Your profile:
6+ years of hands-on experience in data engineering and large-scale distributed systems,
proven expertise in building and maintaining complex ETL/ELT pipelines,
deep knowledge of orchestration frameworks (Airflow) and workflow optimization,
strong GCP cloud infrastructure experience,
GKE experience,
expert-level programming in Python or Scala,
solid understanding of Spark internals,
experience with CI/CD tools (e.g., Jenkins, GitHub Actions) and infrastructure as code,
familiarity with managing self-hosted tools like Spark or Airflow on Kubernetes,
experience managing data warehouse in BigQuery,
strong communication skills and a proactive, problem-solving mindset,
very good command of English (min. C1).
Nice to have:
working experience with messaging systems like Kafka, Redpanda,
experience with real-time data streaming platforms (e.g., Flink, Spark Structured Streaming),
familiarity with ML platforms or MLOps workflows,
familiarity with Kubeflow, Valido, Looker, Looker Studio.
Work from EU and a work permit to work from EU are required.
Candidates must have an active VAT status in the EU VIES registry: https://ec.europa.eu/taxation_customs/vies/
Recruitment Process:
CV review – HR call – Technical Interview (with Live-coding) – Client Interview (with Live-coding) – Hiring Manager Interview - Decision
