GetInData | Part of Xebia is a leading data company working for international Clients, delivering innovative projects related to Data, AI, Cloud, Analytics, ML/LLM, and GenAI. The company was founded in 2014 by data engineers and today brings together 120 Data & AI experts. Our Clients are both fast-growing scaleups and large corporations that are industry leaders. In 2022, we joined forces with Xebia Group to broaden our horizons and bring new international opportunities.
What about the projects we work with?
We run a variety of projects in which our sweepmasters can excel. Advanced Analytics, Data Platforms, Streaming Analytics Platforms, Machine Learning Models, Generative AI and more. We like working with top technologies and open-source solutions for Data & AI and ML/AI. In our portfolio, you can find Clients from many industries, e.g., media, e-commerce, retail, fintech, banking, and telcos, such as Truecaller, Spotify, ING, Acast, Volt, Play, and Allegro. You can read some customer stories here.
What else do we do besides working on projects?
We conduct many initiatives like Guilds and Labs and other knowledge-sharing initiatives. We build a community around Data & AI, thanks to our conference Big Data Technology Warsaw Summit, meetup Warsaw Data Tech Talks, Radio Data podcast, and DATA Pill newsletter.
Data & AI projects that we run and the company's philosophy of sharing knowledge and ideas in this field make GetInData | Part of Xebia not only a great place to work but also a place that provides you with a real opportunity to boost your career.
If you want to be up to date with the latest news from us, please follow up on our LinkedIn profile.
About role
We are excited to announce that we are seeking an Analytics Engineer! This is a vital role in our company, and we are looking for candidates with exceptional personality and experience. While we do not have an immediate project available for this position, we invite you to contact us to discuss potential future opportunities.
The Analytics Engineer's goal is to manage the entire data value chain, from data sources to business insights.
An Analytics Engineer is responsible for collecting business requirements, modeling data, building data pipelines, creating data visualizations, and helping businesses make decisions based on this data. You can use various technologies covering the full data life cycle and work with different kinds of datasets.
An Analytics Engineer often understands both business and technology and is a good communicator who can help them understand each other. He/she can turn business requirements into working data products (like reports and analysis), often in cooperation with different stakeholders.
Responsibilities
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