Data Engineer

Required Skills & Qualifications:

• Strong expertise in Azure Databricks, Python, and Spark (must-have). 
• Solid experience with Azure Data Services, such as:Azure Data Lake and Azure Data Factory 
• Experience in ingestion tools like: Qlik Recplicate / MQ / MQCC 
• Experience with API development (REST/JSON or equivalent). 
• Solid understanding of ETL processes, data modeling, and fundamental data architecture principles. 
• Familiarity with CI/CD pipelines and version control (Git, etc.). 
• Strong problem‑solving skills and structured way of working within an agile delivery model. 
• Excellent communication and collaboration skills - you enjoy interacting with business stakeholders and cross-functional teams. 

Nice-to-Have Skills 

• Experience with big data processing and performance tuning in Spark. 
• Knowledge of data governance, lineage, and security best practices. 
• Exposure to Power BI or similar visualization tools. 

Data Engineer

Location: hybrid, 2-3 days per week in the Wrocław office Salary: 130 PLN/h B2B

This role is hands-on, highly collaborative, and ideal for someone who enjoys turning complex data challenges into reliable, production-grade solutions.

Offer:

• Multisport Card 
• Life insurance 
• Private healthcare 
• PowerYou platform 

Opis Firmy

Experis to światowy lider rekrutacji specjalistów i kadry zarządzającej w kluczowych obszarach IT. Z nami znajdziesz konkurencyjne oferty zatrudnienia oraz ciekawe projekty IT skierowane zarówno do ekspertów z wieloletnim doświadczeniem, jak i osób, które dopiero zaczynają swoją przygodę w branży IT.

Oferujemy rekrutacje menedżerów i wysoko wykwalifikowanych konsultantów z doświadczeniem w branży IT. Experis jest częścią ManpowerGroup i został uznany za jedną z najbardziej etycznych firm na świecie.

,[Design, develop, and optimize data pipelines and workflows using Azure Databricks and Python. , Implement and maintain data solutions across the Azure Data Platform (Data Lake, Data Factory, Databricks, etc.). , Develop and maintain APIs supporting data ingestion, data sharing, and interoperability. , Collaborate closely with business stakeholders to gather requirements and translate them into technical solutions. , Ensure data quality, security, and compliance across all solutions. , Integrate data solutions into existing business processes and cross-functional systems. , Continuously improve performance, cost-efficiency, and scalability of data systems. ] Requirements: Data pipelines, Azure Databricks, Data Lake, Databricks, Security, Python, Spark, Azure Data, Azure Data Factory, Qlik, IBM MQ, API, REST API, JSON, ETL, Data modeling, CI/CD Pipelines, Git, Agile, Big data, Performance tuning, Power BI Additionally: Sport Subscription, Private healthcare, Life insurance.