Senior Analytics Engineer (Databricks)

 Posted 5 hours ago
     
5-10 years experience
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AI Summary

Build and refine the analytical layer on top of the data platform to support CRM sourced data. Translate source system data into business-friendly analytical structures and curated datasets for reporting.

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

 

You will be:

  • building and refining the analytical layer on top of the data platform supporting CRM sourced data,
  • preparing data models and curated datasets for analytics and reporting,
  • working closely with Data Engineering and Architecture stakeholders on data readiness and usability,
  • translating source system data into business friendly analytical structures,
  • supporting quality, consistency, and usability of analytics ready datasets.

Your profile:

  • proven experience in an Analytics Engineer, Analytics Developer, or highly technical BI / data modelling role,
  • strong SQL skills,
  • experience working with modern cloud data platforms, preferably Databricks,
  • experience modelling analytical datasets for reporting and business consumption,
  • ability to work closely with Data Engineers and business stakeholders,
  • experience with Azure based data environments,
  • experience working with CRM sourced data or other business application data,
  • understanding of upstream ingestion and transformation processes,
  • familiarity with semantic modelling, dimensional modelling, or analytics focused data design,
  •  experience improving data usability, consistency, and reporting readiness.

Work from the European Union region and a work permit are required.

Nice to have:

  • experience with BI tools and reporting environments,
  • basic Python knowledge for working with data,
  • familiarity with orchestration or workflow driven data environments,
  • experience in enterprise or regulated environments,
  • exposure to energy, utilities, or similar business domains.

Recruitment Process:

CV review – HR call – Technical InterviewClient Interview – Decision

 

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