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IONOS

Data Engineer, Databricks, Access & Business Intelligence

IONOS

Data Engineer responsible for developing scalable data pipelines using Azure Databricks. Collaborating with teams to ensure data reliability and performance for IONOS' cloud services.

Posted 4/27/2026full-timeBucharest • 🇷🇴 RomaniaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies
AzureCloudMS SQL ServerPySparkSQLVault

About the role

Key responsibilities & impact
  • 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

Requirements

What you’ll need
  • 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.

Benefits

Comp & perks
  • 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.

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Hard Skills & Tools
Azure DatabricksPySparkSQLData FactoryData Lake StorageAzure SQLMS SQL ServerSSASPower BIdata transformation
Soft Skills
collaborationrequirement analysiseffort estimationproblem-solvingcommunication