Senior Data Engineer

🔍 Senior Data Engineer | Multiple Data Projects

Location: Remote / Hybrid, depending on the project
Contract type: B2B
Capacity: Full-time
Projects: Multiple long-term Data & Analytics projects

🚀 About the projects

We 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 are

Kyotu 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 pipelines

• develop and maintain modern Data Warehouse, Data Lake and Lakehouse solutions

• build scalable data processing solutions in Azure or AWS

• work with platforms such as Databricks or Microsoft Fabric

• integrate data from databases, APIs, files and enterprise systems

• develop data transformation and ingestion processes

• work with batch, streaming and event-driven data pipelines

• design and implement data models

• optimize data processing performance and reliability

• ensure data quality, security and governance

• support modernization and migration from legacy or on-premises environments to cloud platforms

• implement monitoring and alerting for data pipelines

• participate in code reviews and technical design discussions

• work with Git, CI/CD and DevOps practices

• collaborate with Data Architects, BI teams, analysts and business stakeholders

🧩 Must haves

• minimum 5 years of commercial experience in Data Engineering or a similar data-focused role

• very good knowledge of SQL

• commercial experience with Python or another programming language used in Data Engineering

• strong understanding of ETL/ELT and data pipeline development

• experience with Data Warehouse, Data Lake or Lakehouse architectures

• experience with data integration and transformation

• good understanding of data modeling

• experience working with cloud or enterprise data platforms

• experience with Git and CI/CD

• good understanding of data quality, security and production-grade data processing

• ability to independently solve complex technical problems

• good communication skills and ability to work with technical and business stakeholders

• good 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 layers

AWS Data Engineering
AWS 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 Management

• streaming and event-driven architectures

• Infrastructure as Code

• test automation

• migrations from On-Premises to Cloud

• experience with more than one cloud platform: Azure, AWS or GCP

• Snowflake or BigQuery

• Power BI

• AI / Machine Learning data workloads

• experience in regulated or enterprise environments such as banking or energy

📦 What we offer

• B2B cooperation

• full-time projects

• remote and hybrid opportunities, depending on the project

• access to several Data Engineering projects with different technology stacks

• long-term cooperation opportunities

• projects for large enterprise clients

• possibility to work with modern Cloud, Data and AI technologies

• opportunity to match the project to your strongest technology stack and experience

• collaboration with experienced Data Engineers, Architects and technical teams