Senior Data Engineer

🔍 Senior Data Engineer | Multiple Data Projects

• Location: Remote / Hybrid, depending on the project
• Contract type: B2BCapacity: Full-time
• Projects: Multiple long-term Data & Analytics projects🚀 About the projectsWe are looking for experienced Senior Data Engineers to join several ongoing and upcoming Data & Analytics projects for enterprise clients across different industries.

The projects vary in terms of technology stack and architecture. Depending on your experience, you may work with Azure, AWS, Microsoft Fabric, Databricks, modern Lakehouse platforms, or enterprise data environments.

You are not expected to know all of the technologies listed below.

We are looking for engineers with strong Data Engineering fundamentals and solid commercial experience in at least one modern data technology stack.

Depending on the project, your work may involve building scalable data pipelines, developing Data Lake / Lakehouse platforms, modernizing legacy data environments, implementing cloud-based data solutions, or preparing data for BI, analytics and AI use cases.💡 Who we areKyotu Technology is a boutique software house based in Wrocław and Warsaw, working fully remotely or in hybrid mode across Poland. We focus on long-term, high-quality engineering and building production-grade systems with real business impact.🧠 Your responsibilities

• Depending on the project and your specialization, your responsibilities may include:design, build and optimize ETL/ELT pipelinesdevelop and maintain modern Data Warehouse, Data Lake and Lakehouse solutionsbuild scalable data processing solutions in Azure or AW
• Swork with platforms such as Databricks or Microsoft Fabricintegrate data from databases, APIs, files and enterprise systemsdevelop data transformation and ingestion processeswork with batch, streaming and event-driven data pipelinesdesign and implement data modelsoptimize data processing performance and reliabilityensure data quality, security and governancesupport modernization and migration from legacy or on-premises environments to cloud platformsimplement monitoring and alerting for data pipelinesparticipate in code reviews and technical design discussionswork with Git, CI/CD and DevOps practicescollaborate with Data Architects, BI teams, analysts and business stakeholders🧩 Must havesminimum 5 years of commercial experience in Data Engineering or a similar data-focused rolevery good knowledge of SQ
• Lcommercial experience with Python or another programming language used in Data Engineeringstrong understanding of ETL/ELT and data pipeline developmentexperience with Data Warehouse, Data Lake or Lakehouse architecturesexperience with data integration and transformationgood understanding of data modelingexperience working with cloud or enterprise data platformsexperience with Git and CI/CDgood understanding of data quality, security and production-grade data processingability to independently solve complex technical problemsgood communication skills and ability to work with technical and business stakeholdersgood command of English
• Additionally, we are looking for strong commercial experience in at least one of the following technology areas:

Microsoft Data Stack

• Azure Data Platform / Microsoft Fabric / SQL Server / SSIS / SSAS
• Databricks & Lakehouse
• Databricks / Lakehouse / Medallion Architecture / Bronze, Silver & Gold layersAWS Data EngineeringAWS data services / Data Lake / Lakehouse / cloud-native data pipelines
• Modern Data Pipelines
• Airflow / dbt / orchestration / transformation frameworks
• Enterprise Data Integration
• Oracle / SAP Data Services / SAP IQ / enterprise integration platforms
• Again, you do not need experience with all of the above stacks. We will match your experience and specialization with the most suitable project.✨ Nice to have
• Depending on the project, experience in any of the following areas will be an advantage:

Data Mesh and Data Products

• Data Governance
• Data Quality
• Metadata Management and Data Lineage
• Master Data Managementstreaming and event-driven architectures
• Infrastructure as Codetest automationmigrations from On-Premises to Cloudexperience with more than one cloud platform: Azure, AWS or GCP
• Snowflake or BigQuery
• Power BIAI / Machine Learning data workloadsexperience in regulated or enterprise environments such as banking or energy📦 What we offerB2B cooperationfull-time projectsremote and hybrid opportunities, depending on the projectaccess to several Data Engineering projects with different technology stackslong-term cooperation opportunitiesprojects for large enterprise clientspossibility to work with modern Cloud, Data and AI technologiesopportunity to match the project to your strongest technology stack and experiencecollaboration with experienced Data Engineers, Architects and technical teams