Senior Data Engineer

Quick Facts

• Role: Senior Data Engineer
• Projects: Multiple long-term Data & Analytics projects
• Work model: Remote / Hybrid (depending on project)
• Cooperation: B2B, full-time

Description

You’ll join ongoing and upcoming enterprise Data & Analytics projects and work on building, optimizing, and modernizing production-grade data platforms and pipelines. Project stacks vary (Azure/AWS, Microsoft Fabric, Databricks, Lakehouse platforms, and enterprise data environments). You’re not expected to know every listed technology—focus on strong fundamentals plus proven commercial experience in at least one modern data stack.

Responsibilities

• Design, build, and optimize ETL/ELT pipelines
• Develop and maintain Data Warehouse, Data Lake, and Lakehouse solutions
• Build scalable data processing solutions on Azure or AWS
• Work with Databricks or Microsoft Fabric platforms
• Integrate data from databases, APIs, files, and enterprise systems
• Develop data transformation and ingestion processes
• Build batch, streaming, and event-driven data pipelines
• Design and implement data models
• Optimize data processing performance and reliability; ensure data quality
• Implement data security and governance
• Support modernization/migration from legacy/on-prem to cloud
• Implement monitoring and alerting for data pipelines
• Participate in code reviews and technical design discussions
• Use Git, CI/CD, and DevOps practices
• Collaborate with Data Architects, BI teams, analysts, and business stakeholders

Requirements (Must haves)

• Minimum 5 years of commercial experience in Data Engineering (or similar)
• Very good SQL knowledge
• Commercial experience with Python (or another Data Engineering language)
• Strong ETL/ELT and data pipeline development fundamentals
• Experience with Data Warehouse, Data Lake, or Lakehouse architectures
• Experience with data integration and transformation
• Good data modeling knowledge
• Experience with cloud or enterprise data platforms
• Experience with Git and CI/CD
• Understanding of data quality, security, and production-grade processing
• Ability to independently solve complex technical problems
• Good communication skills and ability to work with technical and business stakeholders
• Good command of English
• Strong commercial experience in at least one stack: Microsoft Data Stack (Azure Data Platform/Microsoft Fabric/SQL Server/SSIS/SSAS), Databricks & Lakehouse (Databricks/Lakehouse/Medallion Bronze-Silver-Gold), AWS Data Engineering (AWS data services/Data Lake/Lakehouse/cloud-native pipelines), Modern Data Pipelines (Airflow/dbt/orchestration/transformation frameworks), or Enterprise Data Integration (Oracle/SAP Data Services/SAP IQ/enterprise integration platforms)

Benefits

• B2B cooperation and full-time projects
• Remote and hybrid options depending on the project
• Access to multiple Data Engineering projects with different technology stacks
• Long-term cooperation opportunities
• Work for large enterprise clients
• Opportunity to work with modern Cloud, Data, and AI technologies
• Project matching to your strongest technology stack and experience
• Collaboration with experienced Data Engineers, Architects, and technical teams