Middle Databricks Developer with Azure, Data Platform
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Location
Remote (Bulgaria, Cyprus, Poland, Romania, Serbia, Ukraine, Latvia)
Seniority
Middle · 4+ years exp
Visa
Sponsors visas in United States; no register of this country names it
Employment
Full-Time
Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 6, 2026. DataArt scores B on the Alion truth index.
Overview
Company
Impact
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DataArt is a global software engineering and consulting firm headquartered in New York that builds and modernises custom software, data platforms and cloud infrastructure for clients in finance, travel, healthcare, media and retail. Founded in 1997, it runs delivery centres across Europe, the Americas and Asia, including offices in Wroclaw, Lublin and Lodz in Poland and teams in India, and works with more than 400 enterprise clients. Its openings include senior .NET, Java, Python and frontend engineers, DevOps and site reliability engineers, data architects and data engineers, QA automation leads and solution consultants.
We are looking for a Strong Middle / Senior Databricks Developer with Azure to build scalable data platforms, develop complex data pipelines, and support cloud based data engineering solutions.
The Data Platform project focuses on delivering cloud based data engineering solutions in the Microsoft Azure ecosystem. You will work with Databricks, Spark, and Azure services to build and optimize reliable data pipelines and support modern Lakehouse architecture.
- Design data solutions using Databricks
- Develop data pipelines for structured and unstructured data
- Build ETL and ELT workflows in Azure
- Develop high performance solutions using PySpark and Spark SQL
- Design Lakehouse architectures using Delta Lake
- Integrate data from databases APIs cloud services and streaming platforms
- Optimize Spark workloads for performance scalability and cost efficiency
- Ensure data quality governance security and monitoring standards
- Collaborate with Data Engineers Data Architects Analytics teams and business stakeholders
- Participate in architectural discussions and technical decision making
- Support CI and CD processes and infrastructure automation practices
- 4+ years of experience in Data Engineering
- 3+ years of hands on experience with Azure Databricks
- Experience with Apache Spark and PySpark
- Knowledge of Python and SQL
- Experience with Azure Data Factory
- Experience with Azure Data Lake Storage Gen2
- Experience with Delta Lake and Lakehouse architecture
- Experience implementing end to end data pipelines in Azure
- Understanding of data modeling principles and best practices
- Experience working with large scale datasets in cloud environments
- Experience with Git based version control systems
- Upper Intermediate or higher English level
- Experience optimizing Spark workloads
- Experience collaborating with cross functional technical and business teams
- Experience supporting CI and CD processes
- Experience with infrastructure automation practices
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