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 committed to leading the way in business and artificial intelligence, utilizing state-of-the-art tools and methodologies. You’ll merge traditional data engineering with modern natural language processing. This role involves leveraging tools like Databricks, BigQuery, Airflow, Vertex AI, ElasticSearch, and integrating LLM APIs from major platforms such as OpenAI.
Responsibilities
Developing and maintaining scalable data pipelines using tools such as Databricks, Airflow,
Developing text data and language processing pipelines employing Elasticsearch, Langchain, LlamaIndex, or cloud-native services
Implementing knowledge-retrieval systems, semantic search, or vector stores using e.g. Elasticsearch
Integrating APIs of LLMs (e.g., OpenAI API) to build AI-based applications like conversational search or chatbots
Applying tools for comprehensive data analytics on both structured and unstructured data for BI purposes, as well as AI-enabled features
Keeping abreast of the latest trends and advancements in data engineering, machine learning, and AI
