Senior GCP Data Engineer (Future Opening)
Who We Are
While Xebia is a global tech company, our journey in CEE started with two Polish companies – 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.
About the role:
As a Data Engineer at Xebia, you will work closely with engineering, product, and data teams to deliver our clients scalable and robust data solutions. Your key responsibilities will include designing, building, and maintaining data platforms and pipelines and mentoring new engineers.
You will be:
developing and maintaining data pipelines to ensure seamless data flow from the Loyalty system to the data lake and data warehouse,
collaborating with data engineers to ensure data engineering best practices are integrated into the development process,
ensuring data integrity, consistency, and availability across all data systems,
integrating data from various sources, including transactional databases, third-party APIs, and external data sources, into the data lake,
implementing ETL processes to transform and load data into the data warehouse for analytics and reporting,
working closely with cross-functional teams including Engineering, Business Analytics, Data Science and Product Management to understand data requirements and deliver solutions,
optimizing data storage and retrieval to improve performance and scalability,
monitoring and troubleshooting data pipelines to ensure high reliability and efficiency,
implementing and enforcing data governance policies to ensure data security, privacy, and compliance,
developing documentation and standards for data processes and procedures.