Informacje o stanowisku

We are looking for an accomplished Senior Azure Data Engineer to support the design, migration, and optimization of large-scale data platforms within regulated industries. This role focuses on leading complex migrations from on-premise environments such as Cloudera and Hadoop to modern Azure-based lakehouse architectures. The position combines hands-on engineering with architectural ownership, automation, and team leadership. The successful candidate will play a key role in delivering scalable, secure, and production-ready data solutions.

• At least 5 years of experience in data engineering, including working with large-scale data platforms
• Strong hands-on experience with Python, PySpark, SQL, and SparkSQL
• Proven expertise in Azure Databricks, Azure Data Factory, and Delta Lake
• Solid understanding of ETL/ELT design, medallion architecture, and metadata-driven frameworks
• Experience with CI/CD pipelines, Azure DevOps, GitHub, Jenkins, and infrastructure as code
• Willingness to work from the Warsaw office 2–3 days per week
• Fluent Polish required
• Residing in Poland required

We are looking for an accomplished Senior Azure Data Engineer to support the design, migration, and optimization of large-scale data platforms within regulated industries. This role focuses on leading complex migrations from on-premise environments such as Cloudera and Hadoop to modern Azure-based lakehouse architectures. The position combines hands-on engineering with architectural ownership, automation, and team leadership. The successful candidate will play a key role in delivering scalable, secure, and production-ready data solutions.

,[Leading end-to-end migration of on-premise data platforms to Azure Databricks, Designing lakehouse architectures using medallion principles and Delta Lake, Building metadata-driven ingestion, transformation, and data quality pipelines, Automating orchestration and deployment through CI/CD pipelines and DevOps tooling, Optimizing Spark and PySpark pipelines for performance, reliability, and cost efficiency, Mentoring data engineering teams and promoting cloud-native best practices Requirements: Databricks, Cloudera, Apache Hadoop, Data Lake, Data Vault, Python, ADF, ETL, CI/CD, Oracle Applications, MS SQL Server

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