4+ years of experience in data engineering or similar roles.
2+ years hands-on experience with Databricks in production environments.
Deep knowledge of Apache Spark and distributed processing concepts .
Proficiency in Python and SQL .
Practical experience with Microsoft Azure cloud ecosystems.
Familiarity with Data Lake solutions and data pipeline design .
Good communication skills and proficiency in both English and Polish (required).
Nice to Have:
Experience with Hive or Impala .
Familiarity with Machine Learning pipelines , CI/CD for data workloads.
Previous experience working in large-scale enterprise environments .
Joining this project you’ll become part of Mindbox – a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’ll back you up every step of the way, accelerate your development, and ensure your skills make a difference.
At Mindbox we connect top IT talents with technology projects for leading enterprises across Europe.
Join Our Client as a Databricks Engineer!
We are looking for a Mid/Senior Databricks Engineer to design and develop scalable data processing and integration solutions within an Azure environment. If you have strong experience in building data pipelines , working with Apache Spark , and modern cloud technologies, this role is for you!
Sounds like your kind of challenge?
#LI-Hybrid - 1- 2 times a week in the Warsaw office (depending on the manager)
What you get in return
Flexible cooperation model
Hybrid work setup – 1-2 times a week in the Warsaw office (depending on the manager) - remote days available depending on the client’s arrangements
Collaborative team culture – work alongside experienced professionals eager to share knowledge
Continuous development – access to training platforms and growth opportunities
Comprehensive benefits – including Interpolska Health Care, Multisport card, Warta Insurance, and more
High quality equipment – laptop and essential software provided
,[Design and build advanced data solutions on Azure Databricks., Develop and maintain data pipelines using Python and SQL., Perform distributed data processing leveraging Apache Spark., Optimize Spark jobs, queries, and workflows for performance., Integrate solutions with Data Lake environments., Monitor and troubleshoot data flows and processes for stability., Participate in code reviews and cooperate with data & analytics teams.] Requirements: Databricks, Spark, Azure Cloud, Communication skills, Hive, CD
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