Design, implement, and maintain scalable data pipelines and workflows using Azure Databricks and the broader Azure data platform (Data Factory, Data Lake Storage, Azure SQL), ensuring reliability, performance, and cost efficiency
Develop and optimize data transformation logic using PySpark and SQL within Databricks, handling large-scale datasets across batch and streaming workloads
Build and maintain data movement procedures, views, and flows for both frontend and backend systems, leveraging MS SQL Server, SSAS, Power BI, and Azure cloud services
Collaborate closely with BI analysts and architects to translate business requirements into robust data engineering solutions; implement new ideas and improvements driven by that collaboration
Perform requirement analyses and effort estimations within projects and deliver solutions as part of an international team
Support Business Analysts with ad-hoc analyses on large data volumes, complex data models, and data extraction from operational systems
Design, code, test, debug, document, and support all types of data flows and transformation procedures consistent with established specifications and business requirements to deliver maximum business value
Support, enhance, and modify existing applications, codebases, and data pipelines

Solid experience with Azure Databricks — notebook development, job orchestration, cluster management, Delta Lake
Experience with the Azure cloud platform — Data Factory, Data Lake Storage Gen2, Azure SQL, Key Vault, and related services
Strong proficiency in SQL and PySpark, with the ability to write performant, production-grade code against large data volumes
Well-rounded knowledge of data warehousing and Business Intelligence concepts, physical data modeling techniques, and the specific requirements of data warehouse architectures
Knowledge of physical database implementation and performance tuning based on logical data models
Ability to collaborate effectively with team members and cross-functional stakeholders.

Access to local/international trainings, development and growth opportunities, including access to e-learning platforms, covering both technical and soft skills areas;
Modern technologies, product responsibility;
Flexible work schedule;
Hybrid work option;
Medical services package from one of two private providers;
25 vacation days per year;
Substitute days off for public holidays that occur on the weekend;
Meal tickets;
Internal referral program;
Team events, networking events organized to promote a passionate, creative and diverse culture;
Summerfest and Winterfest parties;
Of course, coffee, soft drinks and fresh fruits are on us in the office.

Data Engineer, Databricks, Access & Business Intelligence

Key skills